Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Sentry's Python SDK are vulnerable to unintentional exposure of environment variables to subprocesses despite the env={} setting. In Python's 'subprocess' calls, all environment variables are passed to subprocesses by default. However, if you specifically do not want them to be passed to subprocesses, you may use 'env' argument in 'subprocess' calls. Due to the bug in Sentry SDK, with the Stdlib integration enabled (which is enabled by default), this expectation is not fulfilled, and all environment variables are being passed to subprocesses instead. 
As a workaround, and if passing environment variables to child processes poses a security risk for you, you can disable all default integrations.

Sentry-sdk 1.4.1 includes a fix for a Race Condition vulnerability.
https://github.com/getsentry/sentry-python/pull/1203

Sentry-sdk 1.14.0 includes a fix for CVE-2023-28117: When using the Django integration of versions prior to 1.14.0 of the Sentry SDK in a specific configuration it is possible to leak sensitive cookies values, including the session cookie to Sentry. These sensitive cookies could then be used by someone with access to your Sentry issues to impersonate or escalate their privileges within your application. In order for these sensitive values to be leaked, the Sentry SDK configuration must have 'sendDefaultPII' set to 'True'; one must use a custom name for either 'SESSION_COOKIE_NAME' or 'CSRF_COOKIE_NAME' in one's Django settings; and one must not be configured in one's organization or project settings to use Sentry's data scrubbing features to account for the custom cookie names. As of version 1.14.0, the Django integration of the 'sentry-sdk' will detect the custom cookie names based on one's Django settings and will remove the values from the payload before sending the data to Sentry. As a workaround, use the SDK's filtering mechanism to remove the cookies from the payload that is sent to Sentry. For error events, this can be done with the 'before_send' callback method and for performance related events (transactions) one can use the 'before_send_transaction' callback method. Those who want to handle filtering of these values on the server-side can also use Sentry's advanced data scrubbing feature to account for the custom cookie names. Look for the '$http.cookies', '$http.headers', '$request.cookies', or '$request.headers' fields to target with a scrubbing rule.
https://github.com/getsentry/sentry-python/security/advisories/GHSA-29pr-6jr8-q5jm

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563

Affected versions of Flask (≤ 3.1.0) are vulnerable to incorrect fallback key configuration in session signing, leading to stale key usage instead of the intended current key. This flaw undermines session integrity, enabling remote attackers to forge or tamper with cookies via manipulated SECRET_KEY_FALLBACKS parameters. The vulnerability exists in the itsdangerous-based signing routines within flask.sessions (fallback key list ordering).

Flask 2.2.5 and 2.3.2 include a fix for CVE-2023-30861: When all of the following conditions are met, a response containing data intended for one client may be cached and subsequently sent by the proxy to other clients. If the proxy also caches 'Set-Cookie' headers, it may send one client's 'session' cookie to other clients. The severity depends on the application's use of the session and the proxy's behavior regarding cookies. The risk depends on all these conditions being met:
1. The application must be hosted behind a caching proxy that does not strip cookies or ignore responses with cookies.
2. The application sets 'session.permanent = True'
3. The application does not access or modify the session at any point during a request.
4. 'SESSION_REFRESH_EACH_REQUEST' enabled (the default).
5. The application does not set a 'Cache-Control' header to indicate that a page is private or should not be cached.
This happens because vulnerable versions of Flask only set the 'Vary: Cookie' header when the session is accessed or modified, not when it is refreshed (re-sent to update the expiration) without being accessed or modified.
https://github.com/pallets/flask/security/advisories/GHSA-m2qf-hxjv-5gpq

Affected versions of pyjwt are vulnerable to Partial Comparison (CWE-187). This flaw allows attackers to bypass issuer (iss) verification by providing partial matches, potentially granting unauthorized access. The vulnerability arises in the decode method of api_jwt.py, where issuer validation incorrectly treats strings as sequences, leading to partial matches (e.g., "abc" being accepted for "__abc__"). Exploiting this requires crafting JWTs with partially matching iss claims, which is straightforward.

PyJWT 2.4.0 includes a fix for CVE-2022-29217: An attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify 'jwt.algorithms.get_default_algorithms()' to get support for all algorithms, or specify a single algorithm. The issue is not that big as 'algorithms=jwt.algorithms.get_default_algorithms()' has to be used. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding.

Celery 5.2.0 updates 'kombu' to v5.2.1, which includes dependencies updates that resolve security issues.

Celery 5.2.2 includes a fix for CVE-2021-23727: Celery before 5.2.2. by default trusts the messages and metadata stored in backends (result stores). When reading task metadata from the backend, the data is deserialized. Given that an attacker can gain access to, or somehow manipulate the metadata within a celery backend, they could trigger a stored command injection vulnerability and potentially gain further access to the system.

Affected versions of Black are vulnerable to Regular Expression Denial of Service (ReDoS) via the lines_with_leading_tabs_expanded function in the strings.py file. An attacker could exploit this vulnerability by crafting a malicious input that causes a denial of service.

Werkzeug is a comprehensive WSGI web application library. The debugger in affected versions of Werkzeug can allow an attacker to execute code on a developer's machine under some circumstances. This requires the attacker to get the developer to interact with a domain and subdomain they control, and enter the debugger PIN, but if they are successful it allows access to the debugger even if it is only running on localhost. This also requires the attacker to guess a URL in the developer's application that will trigger the debugger.

Affected versions of Werkzeug are vulnerable to Path Traversal (CWE-22) on Windows systems running Python versions below 3.11. The safe_join() function failed to properly detect certain absolute paths on Windows, allowing attackers to potentially access files outside the intended directory. An attacker could craft special paths starting with "/" that bypass the directory restrictions on Windows systems. The vulnerability exists in the safe_join() function which relied solely on os.path.isabs() for path validation. This is exploitable on Windows systems by passing paths starting with "/" to safe_join(). To remediate, upgrade to the latest version which includes additional path validation checks. 
NOTE: This vulnerability specifically affects Windows systems running Python versions below 3.11 where ntpath.isabs() behavior differs.

Werkzeug 2.2.3 includes a fix for CVE-2023-23934: Browsers may allow "nameless" cookies that look like '=value' instead of 'key=value'. A vulnerable browser may allow a compromised application on an adjacent subdomain to exploit this to set a cookie like '=__Host-test=bad' for another subdomain. Werkzeug prior to 2.2.3 will parse the cookie '=__Host-test=bad' as __Host-test=bad'. If a Werkzeug application is running next to a vulnerable or malicious subdomain which sets such a cookie using a vulnerable browser, the Werkzeug application will see the bad cookie value but the valid cookie key.
https://github.com/pallets/werkzeug/security/advisories/GHSA-px8h-6qxv-m22q

Werkzeug is a comprehensive WSGI web application library. If an upload of a file that starts with CR or LF and then is followed by megabytes of data without these characters: all of these bytes are appended chunk by chunk into internal bytearray and lookup for boundary is performed on growing buffer. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests.

Werkzeug 3.0.1 and 2.3.8 include a security fix: Slow multipart parsing for large parts potentially enabling DoS attacks.
https://github.com/pallets/werkzeug/commit/b1916c0c083e0be1c9d887ee2f3d696922bfc5c1

Affected versions of Werkzeug are potentially vulnerable to resource exhaustion when parsing file data in forms. Applications using 'werkzeug.formparser.MultiPartParser' to parse 'multipart/form-data' requests (e.g. all flask applications) are vulnerable to a relatively simple but effective resource exhaustion (denial of service) attack. A specifically crafted form submission request can cause the parser to allocate and block 3 to 8 times the upload size in main memory. There is no upper limit; a single upload at 1 Gbit/s can exhaust 32 GB of RAM in less than 60 seconds.

Werkzeug 2.2.3 includes a fix for CVE-2023-25577: Prior to version 2.2.3, Werkzeug's multipart form data parser will parse an unlimited number of parts, including file parts. Parts can be a small amount of bytes, but each requires CPU time to parse and may use more memory as Python data. If a request can be made to an endpoint that accesses 'request.data', 'request.form', 'request.files', or 'request.get_data(parse_form_data=False)', it can cause unexpectedly high resource usage. This allows an attacker to cause a denial of service by sending crafted multipart data to an endpoint that will parse it. The amount of CPU time required can block worker processes from handling legitimate requests. The amount of RAM required can trigger an out of memory kill of the process. Unlimited file parts can use up memory and file handles. If many concurrent requests are sent continuously, this can exhaust or kill all available workers.
https://github.com/pallets/werkzeug/security/advisories/GHSA-xg9f-g7g7-2323

Gunicorn version 21.2.0 does not properly validate the value of the 'Transfer-Encoding' header as specified in the RFC standards, which leads to the default fallback method of 'Content-Length,' making it vulnerable to TE.CL request smuggling. This vulnerability can lead to cache poisoning, data exposure, session manipulation, SSRF, XSS, DoS, data integrity compromise, security bypass, information leakage, and business logic abuse.

Gunicorn fails to properly validate Transfer-Encoding headers, leading to HTTP Request Smuggling (HRS) vulnerabilities. By crafting requests with conflicting Transfer-Encoding headers, attackers can bypass security restrictions and access restricted endpoints. This issue is due to Gunicorn's handling of Transfer-Encoding headers, where it incorrectly processes requests with multiple, conflicting Transfer-Encoding headers, treating them as chunked regardless of the final encoding specified. This vulnerability allows for a range of attacks including cache poisoning, session manipulation, and data exposure.

A time-based vulnerability in Gunicorn affected versions allows an attacker to disrupt service by manipulating the system clock, causing premature worker timeouts and potential denial-of-service (DoS) conditions. The issue stems from the use of time.time() in the worker timeout logic, which can be exploited if an attacker gains the ability to change the system time.

corydolphin/flask-cors is vulnerable to log injection when the log level is set to debug. An attacker can inject fake log entries into the log file by sending a specially crafted GET request containing a CRLF sequence in the request path. This vulnerability allows attackers to corrupt log files, potentially covering tracks of other attacks, confusing log post-processing tools, and forging log entries. The issue is due to improper output neutralization for logs. See CVE-2024-1681.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows the `Access-Control-Allow-Private-Network` CORS header to be set to true by default. This behavior can expose private network resources to unauthorized external access, leading to significant security risks such as data breaches, unauthorized access to sensitive information, and potential network intrusions.

corydolphin/flask-cors version 4.0.1 contains an improper regex path matching vulnerability. The plugin prioritizes longer regex patterns over more specific ones when matching paths, which can lead to less restrictive CORS policies being applied to sensitive endpoints. This mismatch in regex pattern priority allows unauthorized cross-origin access to sensitive data or functionality, potentially exposing confidential information and increasing the risk of unauthorized actions by malicious actors.

Flask-CORS before 3.0.9 allows ../ directory traversal to access private resources because resource matching does not ensure that pathnames are in a canonical format. See CVE-2020-25032.

A vulnerability in corydolphin/flask-cors version 4.0.1 allows for inconsistent CORS matching due to the handling of the '+' character in URL paths. The request.path is passed through the unquote_plus function, which converts the '+' character to a space ' '. This behavior leads to incorrect path normalization, causing potential mismatches in CORS configuration. As a result, endpoints may not be matched correctly to their CORS settings, leading to unexpected CORS policy application. This can cause unauthorized cross-origin access or block valid requests, creating security vulnerabilities and usability issues.

corydolphin/flask-cors version 4.0.1 contains a vulnerability where the request path matching is case-insensitive due to the use of the try_match function, which is originally intended for matching hosts. This results in a mismatch because paths in URLs are case-sensitive, but the regex matching treats them as case-insensitive. This misconfiguration can lead to significant security vulnerabilities, allowing unauthorized origins to access paths meant to be restricted, resulting in data exposure and potential data leaks.

Sqlalchemy 2.0.0b1 avoids leaking cleartext passwords to the open for careless uses of str(engine.URL()) in logs and prints.
https://github.com/sqlalchemy/sqlalchemy/pull/8563