Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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.

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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.

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Nltk before 3.6.4 is vulnerable to Inefficient Regular Expression Complexity.

Nltk 3.6.5 includes a fix for CVE-2021-43854: Versions prior to 3.6.5 are vulnerable to regular expression denial of service (ReDoS) attacks. The vulnerability is present in PunktSentenceTokenizer, sent_tokenize and word_tokenize. Any users of this class, or these two functions, are vulnerable to the ReDoS attack. In short, a specifically crafted long input to any of these vulnerable functions will cause them to take a significant amount of execution time. If your program relies on any of the vulnerable functions for tokenizing unpredictable user input, it's strongly recommended upgrading to a version of NLTK without the vulnerability. For users unable to upgrade the execution time can be bounded by limiting the maximum length of an input to any of the vulnerable functions.
https://github.com/nltk/nltk/security/advisories/GHSA-f8m6-h2c7-8h9x
https://github.com/nltk/nltk/issues/2866

Nltk before 3.6.6 is vulnerable to Inefficient Regular Expression Complexity.

Affected versions of NLTK are vulnerable to Remote Code Execution if untrusted packages have pickled Python code, and the integrated data package download functionality is used. This affects, for example, averaged_perceptron_tagger and punkt.

Nltk 3.8.1 includes a security fix: A reflected XSS can be achieved by creating a URL, which leads to browser hijacking and sensitive information loss.

Before version 3.8.1 of nltk, if a user opens a malicious link while the wordnet browser is active, it can result in code execution on their system. Influence from a third party to visit a link can possibly lead to remote code execution (RCE).

Nltk 3.6 includes a fix for a REDoS vulnerability.
https://github.com/nltk/nltk/pull/2597

** DISPUTED ** Py throughout 1.11.0 allows remote attackers to conduct a ReDoS (Regular expression Denial of Service) attack via a Subversion repository with crafted info data because the InfoSvnCommand argument is mishandled.
https://github.com/pytest-dev/py/issues/287

Mako before 1.2.2 is vulnerable to Regular expression Denial of Service when using the Lexer class to parse. This also affects babelplugin and linguaplugin.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Tqdm version 4.66.3 addresses CVE-2024-34062, a vulnerability where optional non-boolean CLI arguments like `--delim`, `--buf-size`, and `--manpath` were passed through Python's `eval`, allowing for arbitrary code execution. This security risk, only locally exploitable, has been mitigated in this release. Users are advised to upgrade to version 4.66.3 immediately as there are no workarounds for this issue.

Numpy 1.22.0 includes a fix for CVE-2021-34141: An incomplete string comparison in the numpy.core component in NumPy before 1.22.0 allows attackers to trigger slightly incorrect copying by constructing specific string objects. 
NOTE: the vendor states that this reported code behavior is "completely harmless."
https://github.com/numpy/numpy/issues/18993

Numpy 1.22.2  includes a fix for CVE-2021-41495: Null Pointer Dereference vulnerability exists in numpy.sort in NumPy in the PyArray_DescrNew function due to missing return-value validation, which allows attackers to conduct DoS attacks by repetitively creating sort arrays. 
NOTE: While correct that validation is missing, an error can only occur due to an exhaustion of memory. If the user can exhaust memory, they are already privileged. Further, it should be practically impossible to construct an attack which can target the memory exhaustion to occur at exactly this place.
NOTE2: The specs we include in this advisory differ from the publicly available on other sources. For example, the advisory posted by the NVD indicate that versions up to and including 1.19.0 are affected. However, research by Safety CLI Cybersecurity confirms that the vulnerability remained unaddressed until version 1.22.2.

Numpy 1.21.0rc1 includes a fix for CVE-2021-33430: A Buffer Overflow vulnerability in the PyArray_NewFromDescr_int function of ctors.c when specifying arrays of large dimensions (over 32) from Python code, which could let a malicious user cause a Denial of Service. 
NOTE: The vendor does not agree this is a vulnerability. In (very limited) circumstances a user may be able provoke the buffer overflow, the user is most likely already privileged to at least provoke denial of service by exhausting memory. Triggering this further requires the use of uncommon API (complicated structured dtypes), which is very unlikely to be available to an unprivileged user.
https://github.com/numpy/numpy/issues/18939

Numpy 1.22.0 includes a fix for CVE-2021-41496: Buffer overflow in the array_from_pyobj function of fortranobject.c, which allows attackers to conduct a Denial of Service attacks by carefully constructing an array with negative values. 
NOTE: The vendor does not agree this is a vulnerability; the negative dimensions can only be created by an already privileged user (or internally).
https://github.com/numpy/numpy/issues/19000

An issue in Gevent before version 23.9.0 allows a remote attacker to escalate privileges via a crafted script to the WSGIServer component.

Affected versions of gevent are potentially vulnerable to a Race Condition leading to Unauthorized Access — CWE-362.

Affected versions of gevent were potentially vulnerable to HTTP request smuggling. The issue existed in the pywsgi Input._send_100_continue handling.

Prior to 3.1.6, an oversight in how the Jinja sandboxed environment interacts with the |attr filter allows an attacker that controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to use the |attr filter to get a reference to a string's plain format method, bypassing the sandbox. After the fix, the |attr filter no longer bypasses the environment's attribute lookup. This vulnerability is fixed in 3.1.6.

An oversight in how the Jinja sandboxed environment detects calls to str.format allows an attacker who controls the content of a template to execute arbitrary Python code. To exploit the vulnerability, an attacker needs to control the content of a template. Whether that is the case depends on the type of application using Jinja. This vulnerability impacts users of applications which execute untrusted templates. Jinja's sandbox does catch calls to str.format and ensures they don't escape the sandbox. However, it's possible to store a reference to a malicious string's format method, then pass that to a filter that calls it. No such filters are built-in to Jinja, but could be present through custom filters in an application. After the fix, such indirect calls are also handled by the sandbox.

A vulnerability in the Jinja compiler allows an attacker who can control both the content and filename of a template to execute arbitrary Python code, bypassing Jinja's sandbox protections. To exploit this vulnerability, an attacker must have the ability to manipulate both the template's filename and its contents. The risk depends on the application's specific use case. This issue affects applications that render untrusted templates where the attacker can determine the template filename, potentially leading to severe security breaches.

Jinja is an extensible templating engine. The `xmlattr` filter in affected versions of Jinja accepts keys containing non-attribute characters. XML/HTML attributes cannot contain spaces, `/`, `>`, or `=`, as each would then be interpreted as starting a separate attribute. If an application accepts keys (as opposed to only values) as user input, and renders these in pages that other users see as well, an attacker could use this to inject other attributes and perform XSS. The fix for CVE-2024-22195 only addressed spaces but not other characters. Accepting keys as user input is now explicitly considered an unintended use case of the `xmlattr` filter, and code that does so without otherwise validating the input should be flagged as insecure, regardless of Jinja version. Accepting _values_ as user input continues to be safe.

Jinja is an extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. It is possible to inject arbitrary HTML attributes into the rendered HTML template, potentially leading to Cross-Site Scripting (XSS). The Jinja `xmlattr` filter can be abused to inject arbitrary HTML attribute keys and values, bypassing the auto escaping mechanism and potentially leading to XSS. It may also be possible to bypass attribute validation checks if they are blacklist-based.

Wtforms 3.0.0a1 escape unsafe characters in label text, patching a potential XSS vulnerability.
https://github.com/wtforms/wtforms/commit/8529b953a0919300794f95e01a7713162908c8a6

Pygments 2.15.0 includes a fix for CVE-2022-40896: The regular expressions used when parsing Smithy, SQL/SQL+Jinja, and Java properties files were discovered to be vulnerable. As a result, pygmentizing a maliciously-crafted file of these kinds would have resulted in high resources consumption or crashing of the application.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages-part-2

Sqlparse 0.4.4 includes a fix for CVE-2023-30608: Parser contains a regular expression that is vulnerable to ReDOS (Regular Expression Denial of Service).
https://github.com/andialbrecht/sqlparse/security/advisories/GHSA-rrm6-wvj7-cwh2

Sqlparse 0.5.0 addresses a potential denial of service (DoS) vulnerability related to recursion errors in deeply nested SQL statements. To mitigate this issue, the update replaces recursion errors with a general SQLParseError, improving the resilience and stability of the parsing process.

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.

Requests is an HTTP library. Due to a URL parsing issue, Requests releases prior to 2.32.4 may leak .netrc credentials to third parties for specific maliciously-crafted URLs. Users should upgrade to version 2.32.4 to receive a fix. For older versions of Requests, use of the .netrc file can be disabled with `trust_env=False` on one's Requests Session.

Affected versions of Requests, when making requests through a Requests `Session`, if the first request is made with `verify=False` to disable cert verification, all subsequent requests to the same host will continue to ignore cert verification regardless of changes to the value of `verify`. This behavior will continue for the lifecycle of the connection in the connection pool. Requests 2.32.0 fixes the issue, but versions 2.32.0 and 2.32.1 were yanked due to conflicts with CVE-2024-35195 mitigation.

Affected versions of Requests are vulnerable to proxy credential leakage. When redirected to an HTTPS endpoint, the Proxy-Authorization header is forwarded to the destination server due to the use of rebuild_proxies to reattach the header. This may allow a malicious actor to exfiltrate sensitive information.

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

Validators 0.21.0 includes a fix for CVE-2023-45813: Inefficient Regular Expression Complexity in validate_link.
https://github.com/DedSecInside/TorBot/security/advisories/GHSA-72qw-p7hh-m3ff
https://github.com/python-validators/validators/pull/243

All versions of flask-security are affected by CVE-2021-23385, an open redirect vulnerability: When using the get_post_logout_redirect and get_post_login_redirect functions, it is possible to bypass URL validation and redirect a user to an arbitrary URL by providing multiple back slashes such as \\\evil.com/path. This vulnerability is only exploitable if an alternative WSGI server other than Werkzeug is used, or the default behavior of Werkzeug is modified using 'autocorrect_location_header=False'. 
Note: Flask-Security is not maintained anymore.

Sqlalchemy-utils from version 0.27.0 'EncryptedType' uses by default AES with CBC mode. The IV that it uses is not random though.
https://github.com/kvesteri/sqlalchemy-utils/issues/166
https://github.com/kvesteri/sqlalchemy-utils/pull/499

Python-levenshtein 0.12.1 fixes handling of numerous possible wraparounds in calculating the size of memory allocations. Incorrect handling of which could cause denial of service or even possible remote code execution in previous versions of the library.

Flask-session-captcha 1.2.1 includes a fix for CVE-2022-24880: In versions prior to 1.2.1, the 'captcha.validate()' function would return 'None' if passed no value (e.g. by submitting an having an empty form). If implementing users were checking the return value to be **False**, the captcha verification check could be bypassed. Users can workaround the issue by not explicitly checking that the value is False. Checking the return value less explicitly should still work.
https://github.com/Tethik/flask-session-captcha/security/advisories/GHSA-7r87-cj48-wj45