Redis 4.4.4 and 4.5.4 include a fix for CVE-2023-28859: Redis-py before 4.4.4 and 4.5.x before 4.5.4 leaves a connection open after canceling an async Redis command at an inopportune time, and can send response data to the client of an unrelated request. (This could, for example, happen for a non-pipeline operation.) NOTE: the solutions for CVE-2023-28859 address data leakage across AsyncIO connections in general.
https://github.com/advisories/GHSA-8fww-64cx-x8p5

Redis 4.4.4 and 4.5.4 include a fix for CVE-2023-28859: Redis-py before 4.4.4 and 4.5.x before 4.5.4 leaves a connection open after canceling an async Redis command at an inopportune time, and can send response data to the client of an unrelated request. (This could, for example, happen for a non-pipeline operation.) NOTE: the solutions for CVE-2023-28859 address data leakage across AsyncIO connections in general.
https://github.com/advisories/GHSA-8fww-64cx-x8p5

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Ipywidgets 8.0.0 sanitizes descriptions by default.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

Ipywidgets 8.0.0rc2 makes descriptions plaintext by default for security.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

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

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

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

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

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

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

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

Ipywidgets 8.0.0 sanitizes descriptions by default.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

Ipywidgets 8.0.0rc2 makes descriptions plaintext by default for security.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

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

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

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

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

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

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

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

Ipywidgets 8.0.0 sanitizes descriptions by default.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

Ipywidgets 8.0.0rc2 makes descriptions plaintext by default for security.
https://github.com/jupyter-widgets/ipywidgets/pull/2785

Affected versions of the cryptography package are vulnerable to Improper Certificate Validation due to incomplete enforcement of DNS name constraints on peer names. The certificate validation logic applied DNS name constraints only to Subject Alternative Name (SAN) entries in child certificates, but did not apply the same checks to the peer name presented during validation, which allowed a mismatch between wildcard certificate matching and excluded subtree constraints.

Cryptography 39.0.1 includes a fix for CVE-2023-23931: In affected versions 'Cipher.update_into' would accept Python objects which implement the buffer protocol, but provide only immutable buffers. This would allow immutable objects (such as 'bytes') to be mutated, thus violating fundamental rules of Python and resulting in corrupted output. This issue has been present since 'update_into' was originally introduced in cryptography 1.8.

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography 3.2 and prior are vulnerable to Bleichenbacher timing attacks in the RSA decryption API, via timed processing of valid PKCS#1 v1.5 ciphertext.

Cryptography 3.3.2 includes a fix for CVE-2020-36242: certain sequences of update calls to symmetrically encrypt multi-GB values could result in an integer overflow and buffer overflow, as demonstrated by the Fernet class.

Cryptography 41.0.3 updates its bundled OpenSSL version to include a fix for a Denial of Service vulnerability.
https://github.com/pyca/cryptography/commit/bfa4d95f0f356f2d535efd5c775e0fb3efe90ef2
https://www.openssl.org/news/secadv/20230719.txt

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

The cryptography library has updated its OpenSSL dependency in CI due to security concerns. This vulnerability arises when processing maliciously formatted PKCS12 files, which can cause OpenSSL to crash, leading to a potential Denial of Service (DoS) attack. PKCS12 files, often containing certificates and keys, may come from untrusted sources. The PKCS12 specification allows certain fields to be NULL, but OpenSSL does not correctly handle these cases, resulting in a NULL pointer dereference and subsequent crash. Applications using OpenSSL APIs, such as PKCS12_parse(), PKCS12_unpack_p7data(), PKCS12_unpack_p7encdata(), PKCS12_unpack_authsafes(), and PKCS12_newpass(), are vulnerable if they process PKCS12 files from untrusted sources. Although a similar issue in SMIME_write_PKCS7() was fixed, it is not considered significant for security as it pertains to data writing. This issue does not affect the FIPS modules in versions 3.2, 3.1, and 3.0.

Cryptography 41.0.3  updates its bundled OpenSSL version to include a fix for CVE-2023-2975: AES-SIV implementation ignores empty associated data entries.
https://github.com/pyca/cryptography/commit/bfa4d95f0f356f2d535efd5c775e0fb3efe90ef2
https://www.openssl.org/news/secadv/20230714.txt

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

The `cryptography` library has updated its BoringSSL and OpenSSL dependencies in CI due to a security concern. Specifically, the issue involves the functions `EVP_PKEY_param_check()` and `EVP_PKEY_public_check()`, which are used to check DSA public keys or parameters. These functions can experience significant delays when processing excessively long DSA keys or parameters, potentially leading to a Denial of Service (DoS) if the input is from an untrusted source. The vulnerability arises because the key and parameter check functions do not limit the modulus size during checks, despite OpenSSL not allowing public keys with a modulus over 10,000 bits for signature verification. This issue affects applications that directly call these functions and the OpenSSL `pkey` and `pkeyparam` command-line applications with the `-check` option. The OpenSSL SSL/TLS implementation is not impacted, but the OpenSSL 3.0 and 3.1 FIPS providers are affected by this vulnerability.

Cryptography 41.0.0 updates its dependency 'OpenSSL' to v3.1.1 to include a security fix.
https://github.com/pyca/cryptography/commit/8708245ccdeaff21d65eea68a4f8d2a7c5949a22

Cryptography 41.0.5 updates Windows, macOS, and Linux wheels to be compiled with OpenSSL 3.1.4, that includes a security fix.

Cryptography 3.3 no longer allows loading of finite field Diffie-Hellman parameters of less than 512 bits in length. This change is to conform with an upcoming OpenSSL release that no longer supports smaller sizes. These keys were already wildly insecure and should not have been used in any application outside of testing.
https://github.com/pyca/cryptography/pull/5592

Cryptography version 42.0.5 introduces a limit on the number of name constraint checks during X.509 path validation to prevent denial of service attacks.
https://github.com/pyca/cryptography/commit/4be53bf20cc90cbac01f5f94c5d1aecc5289ba1f

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography 39.0.1 includes a fix for CVE-2022-3996, a DoS vulnerability affecting openssl.
https://github.com/pyca/cryptography/issues/7940

Affected versions of the cryptography package are vulnerable to Improper Input Validation due to missing prime-order subgroup validation for SECT elliptic-curve points. The public_key_from_numbers, EllipticCurvePublicNumbers.public_key(), load_der_public_key(), and load_pem_public_key() entry points accept attacker-supplied public keys without verifying that the provided point lies in the expected prime-order subgroup, enabling small-subgroup points to pass as valid.

Cryptography 41.0.3 updates its bundled OpenSSL version to include a fix for a Denial of Service vulnerability.
https://github.com/pyca/cryptography/commit/b22271cf3c3dd8dc8978f8f4b00b5c7060b6538d
https://www.openssl.org/news/secadv/20230731.txt

The cryptography package before 41.0.2 for Python mishandles SSH certificates that have critical options.

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography 39.0.1 updates its dependency 'OpenSSL' to v3.0.8 to include security fixes.
https://github.com/pyca/cryptography/issues/8229

Cryptography starting from version 42.0.0 updates its CI configurations to use newer versions of BoringSSL or OpenSSL as a countermeasure to CVE-2023-5678. This vulnerability, affecting the package, could cause Denial of Service through specific DH key generation and verification functions when given overly long parameters.

Affected versions of Cryptography may allow a remote attacker to decrypt captured messages in TLS servers that use RSA key exchanges, which may lead to exposure of confidential or sensitive data.

Cryptography 41.0.4 updates Windows, macOS, and Linux wheels to be compiled with OpenSSL 3.1.3, that includes a security fix.
https://github.com/pyca/cryptography/commit/fc11bce6930e591ce26a2317b31b9ce2b3e25512