Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

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

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.

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pyyaml 5.3.1 includes a fix for CVE-2020-1747: A vulnerability was discovered in the PyYAML library in versions before 5.3.1, 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. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

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 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. See CVE-2019-20477. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.

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

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.

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pyyaml 5.3.1 includes a fix for CVE-2020-1747: A vulnerability was discovered in the PyYAML library in versions before 5.3.1, 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. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

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 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. See CVE-2019-20477. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.

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

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.

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 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

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

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 41.0.3 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

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-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

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

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 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 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.

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

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

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

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

Cryptography 41.0.4 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

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pyyaml 5.3.1 includes a fix for CVE-2020-1747: A vulnerability was discovered in the PyYAML library in versions before 5.3.1, 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. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

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 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. See CVE-2019-20477. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.

Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.

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 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.

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

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

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.

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 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

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

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 41.0.3 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

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-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

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

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 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 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.

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

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

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

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

Cryptography 41.0.4 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

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pyyaml 5.3.1 includes a fix for CVE-2020-1747: A vulnerability was discovered in the PyYAML library in versions before 5.3.1, 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. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

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 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. See CVE-2019-20477. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.

Wheel 0.38.1 includes a fix for CVE-2022-40898: An issue discovered in Python Packaging Authority (PyPA) Wheel 0.37.1 and earlier allows remote attackers to cause a denial of service via attacker controlled input to wheel cli.
https://pyup.io/posts/pyup-discovers-redos-vulnerabilities-in-top-python-packages

Sphinx 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.

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 3.0.4 updates jQuery version from 3.4.1 to 3.5.1 for security reasons.

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

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

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.

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 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

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

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 41.0.3 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

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-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

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

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 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 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.

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

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

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

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

Cryptography 41.0.4 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

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

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

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.

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522

Click 8.0.0 uses 'mkstemp()' instead of the deprecated & insecure 'mktemp()'.
https://github.com/pallets/click/issues/1752

Pyyaml 5.3.1 includes a fix for CVE-2020-1747: A vulnerability was discovered in the PyYAML library in versions before 5.3.1, 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. An attacker could use this flaw to execute arbitrary code on the system by abusing the python/object/new constructor.

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 5.1 through 5.1.2 has insufficient restrictions on the load and load_all functions because of a class deserialization issue, e.g., Popen is a class in the subprocess module. See CVE-2019-20477. NOTE: this issue exists because of an incomplete fix for CVE-2017-18342.

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

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.

Pytest-runner depends on deprecated features of setuptools and relies on features that break security mechanisms in pip. For example ‘setup_requires’ and ‘tests_require’ bypass pip --require-hashes. See also pypa/setuptools#1684.
It is recommended that you:
- Remove 'pytest-runner' from your setup_requires, preferably removing the setup_requires option.
- Remove 'pytest' and any other testing requirements from tests_require, preferably removing the tests_requires option.
- Select a tool to bootstrap and then run tests such as tox.
https://github.com/pytest-dev/pytest-runner/blob/289a77b179535d8137118e3b8591d9e727130d6d/README.rst

* Disputed * Scikit-learn 1.1.0rc1 includes a fix for CVE-2020-28975: svm_predict_values in svm.cpp in Libsvm v324, as used in scikit-learn and other products, allows attackers to cause a denial of service (segmentation fault) via a crafted model SVM (introduced via pickle, json, or any other model permanence standard) with a large value in the _n_support array. 
NOTE: the scikit-learn vendor's position is that the behavior can only occur if the library's API is violated by an application that changes a private attribute.

A sensitive data leakage vulnerability was identified in affected versions of scikit-learn TfidfVectorizer. The vulnerability arises from the unexpected storage of all tokens present in the training data within the `stop_words_` attribute, rather than only storing the subset of tokens required for the TF-IDF technique to function. This behavior leads to the potential leakage of sensitive information, as the `stop_words_` attribute could contain tokens that were meant to be discarded and not stored, such as passwords or keys. The impact of this vulnerability varies based on the nature of the data being processed by the vectorizer.

Scikit-learn 0.24.2 includes a fix for a ReDoS vulnerability.
https://github.com/scikit-learn/scikit-learn/issues/19522