** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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.

This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the '_punctuation_re regex' operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory.

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.

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

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

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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.

This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the '_punctuation_re regex' operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory.

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.

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

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

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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.

This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the '_punctuation_re regex' operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory.

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.

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

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

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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.

This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the '_punctuation_re regex' operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory.

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.

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163

** 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

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

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

** 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

Py 1.10.0 includes a fix for CVE-2020-29651: A denial of service via regular expression in the py.path.svnwc component of py (aka python-py) through 1.9.0 could be used by attackers to cause a compute-time denial of service attack by supplying malicious input to the blame functionality.

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 1.21.0rc1 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 1.22.2  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 1.22.0 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

Pylint 2.7.0 includes a fix for vulnerable regular expressions in 'pyreverse'.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pylint 2.13.0 fixes a crash when using the doc_params extension.
https://github.com/PyCQA/pylint/issues/5322

Pylint before 2.6.1 is susceptible to a Regular Expression Denial of Service (ReDoS) vulnerability due to issues in its pyreverse component. This issue arises from certain regular expressions in pyreverse that can be exploited by causing catastrophic backtracking, significantly slowing down the service by forcing it to take a disproportionate amount of time to process inputs. This vulnerability allows attackers to use specially crafted inputs that increase the processing time exponentially, potentially leading to a service becoming inaccessible to legitimate users.
https://github.com/pylint-dev/pylint/commit/5405dd5115d598fa69e49538d50ec79202b1b52e

Pyyaml version 5.4 includes a fix for CVE-2020-14343: A vulnerability was discovered in the PyYAML library in versions before 5.4, where it is susceptible to arbitrary code execution when it processes untrusted YAML files through the full_load method or with the FullLoader loader. Applications that use the library to process untrusted input may be vulnerable to this flaw. This flaw allows an attacker to execute arbitrary code on the system by abusing the python/object/new constructor. This flaw is due to an incomplete fix for CVE-2020-1747.
https://bugzilla.redhat.com/show_bug.cgi?id=1860466

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in inventory.
https://github.com/sphinx-doc/sphinx/issues/8175
https://github.com/sphinx-doc/sphinx/commit/f7b872e673f9b359a61fd287a7338a28077840d2

Sphinx 3.3.0 includes a fix for a ReDoS vulnerability in docstring.
https://github.com/sphinx-doc/sphinx/issues/8172
https://github.com/sphinx-doc/sphinx/commit/f00e75278c5999f40b214d8934357fbf0e705417

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.

This affects the package jinja2 from 0.0.0 and before 2.11.3. The ReDoS vulnerability is mainly due to the '_punctuation_re regex' operator and its use of multiple wildcards. The last wildcard is the most exploitable as it searches for trailing punctuation. This issue can be mitigated by Markdown to format user content instead of the urlize filter, or by implementing request timeouts and limiting process memory.

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.

Ipython versions 8.0.1, 7.31.1, 7.16.3 and 5.11 include a fix for CVE-2022-21699: Affected versions are subject to an arbitrary code execution vulnerability achieved by not properly managing cross user temporary files. This vulnerability allows one user to run code as another on the same machine.
https://github.com/ipython/ipython/security/advisories/GHSA-pq7m-3gw7-gq5x

IPython 8.10.0 includes a fix for CVE-2023-24816: Versions prior to 8.10.0 are subject to a command injection vulnerability with very specific prerequisites. This vulnerability requires that the function 'IPython.utils.terminal.set_term_title' be called on Windows in a Python environment where ctypes is not available. The dependency on 'ctypes' in 'IPython.utils._process_win32' prevents the vulnerable code from ever being reached in the ipython binary. However, as a library that could be used by another tool 'set_term_title' could be called and hence introduce a vulnerability. If an attacker get untrusted input to an instance of this function they would be able to inject shell commands as current process and limited to the scope of the current process. As a workaround, users should ensure that any calls to the 'IPython.utils.terminal.set_term_title' function are done with trusted or filtered input.
https://github.com/ipython/ipython/security/advisories/GHSA-29gw-9793-fvw7

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

Pygments 2.7.4 includes a fix for CVE-2021-20270: An infinite loop in SMLLexer in Pygments versions 1.5 to 2.7.3 may lead to denial of service when performing syntax highlighting of a Standard ML (SML) source file, as demonstrated by input that only contains the "exception" keyword.

Pygments 2.7.4 includes a fix for CVE-2021-27291: In pygments 1.1+, fixed in 2.7.4, the lexers used to parse programming languages rely heavily on regular expressions. Some of the regular expressions have exponential or cubic worst-case complexity and are vulnerable to ReDoS. By crafting malicious input, an attacker can cause a denial of service.

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

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

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

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

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

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

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

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.

Urllib3 is a user-friendly HTTP client library for Python. Starting in version 2.2.0 and before 2.5.0, urllib3 does not control redirects in browsers and Node.js. urllib3 supports being used in a Pyodide runtime, utilizing the JavaScript Fetch API or falling back on XMLHttpRequest. This means Python libraries can be used to make HTTP requests from a browser or Node.js. Additionally, urllib3 provides a mechanism to control redirects, but the retries and redirect parameters are ignored with Pyodide; the runtime itself determines redirect behaviour. This issue has been patched in version 2.5.0.

urllib3 is a user-friendly HTTP client library for Python. Prior to 2.5.0, it is possible to disable redirects for all requests by instantiating a PoolManager and specifying retries in a way that disable redirects. By default, requests and botocore users are not affected. An application attempting to mitigate SSRF or open redirect vulnerabilities by disabling redirects at the PoolManager level will remain vulnerable. This issue has been patched in version 2.5.0.

Urllib3 1.26.17 and 2.0.5 include a fix for CVE-2023-43804: Urllib3 doesn't treat the 'Cookie' HTTP header special or provide any helpers for managing cookies over HTTP, that is the responsibility of the user. However, it is possible for a user to specify a 'Cookie' header and unknowingly leak information via HTTP redirects to a different origin if that user doesn't disable redirects explicitly.
https://github.com/urllib3/urllib3/security/advisories/GHSA-v845-jxx5-vc9f

Urllib3 1.26.5 includes a fix for CVE-2021-33503: When provided with a URL containing many @ characters in the authority component, the authority regular expression exhibits catastrophic backtracking, causing a denial of service if a URL were passed as a parameter or redirected to via an HTTP redirect.
https://github.com/advisories/GHSA-q2q7-5pp4-w6pg

Urllib3's ProxyManager ensures that the Proxy-Authorization header is correctly directed only to configured proxies. However, when HTTP requests bypass urllib3's proxy support, there's a risk of inadvertently setting the Proxy-Authorization header, which remains ineffective without a forwarding or tunneling proxy. Urllib3 does not recognize this header as carrying authentication data, failing to remove it during cross-origin redirects. While this scenario is uncommon and poses low risk to most users, urllib3 now proactively removes the Proxy-Authorization header during cross-origin redirects as a precautionary measure. Users are advised to utilize urllib3's proxy support or disable automatic redirects to handle the Proxy-Authorization header securely. Despite these precautions, urllib3 defaults to stripping the header to safeguard users who may inadvertently misconfigure requests.

Affected versions of urllib3 are vulnerable to an HTTP redirect handling vulnerability that fails to remove the HTTP request body when a POST changes to a GET via 301, 302, or 303 responses. This flaw can expose sensitive request data if the origin service is compromised and redirects to a malicious endpoint, though exploitability is low when no sensitive data is used. The vulnerability affects automatic redirect behavior. It is fixed in versions 1.26.18 and 2.0.7; update or disable redirects using redirects=False.
This vulnerability is specific to Python's urllib3 library.

Selenium 4.15.1 (Python bindings) include a fix for CVE-2023-5590: NULL Pointer Dereference.
https://github.com/seleniumhq/selenium/commit/023a0d52f106321838ab1c0997e76693f4dcbdf6

Affected versions of the virtualenv package are vulnerable to command injection. This vulnerability could allow an attacker to execute arbitrary commands by exploiting improperly quoted string placeholders in activation scripts. The vulnerable functions include various shell activation scripts where placeholders like __VIRTUAL_ENV__ are used. The exploitability depends on the ability to control the input to these placeholders. Users are advised to update to the version where a quoting mechanism has been implemented to mitigate this risk. This vulnerability is specific to environments where shell scripts are used for virtual environment activation. The issue is tracked under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').

Virtualenv version 20.21.0 addresses a race condition in `virtualenv.cli_run` where a `FileNotFoundError` could occur for a JSON file in `pypa/virtualenv/py_info/1`. This error happens if the underlying interpreter is updated, causing the JSON file to be deleted and rewritten.

Prompt-toolkit 3.0.13 fixes a race condition in `ThreadedHistory` which could lead to a deadlock. 
https://github.com/prompt-toolkit/python-prompt-toolkit/commit/99092a8c6d4b411645ac4b84d504e5226e7eebb8#diff-48c0ff10dc3990285d19b3f54e6bfec763089ba1229dc6f9e88463a1046adad7R163