Kushalkhemka/embedding-cve-nvd-dataset huggingface dataset:
CVE ID: CVE-2022-29204 State: PUBLISHED Published: 2022-05-20T22:40:13.000Z Last Updated: 2025-04-22T17:58:11.932Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-191, CWE-20 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the outp
de assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tens
/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx9q-2mx4-m4pg - https://github.com/tensorflow/tensorflow/commit/20cb18724b0bf6c09071a3f53434c4eec53cc147 - https://github.com/tensorflow/tensorflow/commit/84563f265f28b3c36a15335c8b005d405260e943 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L83-L14
CVE ID: CVE-2022-29205 State: PUBLISHED Published: 2022-05-20T22:25:14.000Z Last Updated: 2025-04-22T17:58:30.888Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-908, CWE-476 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_v
2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54ch-gjq5-4976 - https://github.c
eleases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54ch-gjq5-4976 - https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482
CVE ID: CVE-2022-29206 State: PUBLISHED Published: 2022-05-20T22:15:13.000Z Last Updated: 2025-04-22T17:58:39.550Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20, CWE-476 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorDenseAdd` does not fully validate the input arguments. In this case, a reference gets bound to a `nullptr` during kernel execution. This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program
ehavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rc9w-5c64-9vqq - https://github.com/tensorflow/tensorflow/commit/11ced8467eccad9c7cb94867708be8fa5c66c730 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/
8be8fa5c66c730 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse_tensor_dense_add_op.cc
CVE ID: CVE-2022-29207 State: PUBLISHED Published: 2022-05-20T22:10:12.000Z Last Updated: 2025-04-22T17:58:48.272Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20, CWE-475 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid. In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null p
o TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5wpj-c6f7-24x8 -
low/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5wpj-c6f7-24x8 - https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7 - https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498
CVE ID: CVE-2022-29208 State: PUBLISHED Published: 2022-05-20T22:30:13.000Z Last Updated: 2025-04-22T17:58:20.112Z Severity: HIGH (CVSS 7.1 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-787 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.EditDistance` has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service. In multiple places throughout the code, one may compute an index for a write operation. However, the existing validation only checks against the upper bound of the ar
y compute an index for a write operation. However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for `loc`. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/a
8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2r2f-g8mw-9gvr - https://github.com/tensorflow/tensorflow/commit/30721cf564cb029d34535446d6a5a6357bebc8e7
CVE ID: CVE-2022-29209 State: PUBLISHED Published: 2022-05-20T23:25:14.000Z Last Updated: 2025-04-22T17:57:07.814Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-843 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the macros that TensorFlow uses for writing assertions (e.g., `CHECK_LT`, `CHECK_GT`, etc.) have an incorrect logic when comparing `size_t` and `int` values. Due to type conversion rules, several of the macros would trigger incorrectly. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analy
cros would trigger incorrectly. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f4rr-5m7v-wxcw - https://github.com/tensorflow/tensorflow/issues/55530 - https://github.com/tensorflow/tensorflow/pull/55730 - https://github.com/tensorflow/tensorflow/commit/b917181c29b50
30 - https://github.com/tensorflow/tensorflow/pull/55730 - https://github.com/tensorflow/tensorflow/commit/b917181c29b50cb83399ba41f4d938dc369109a1 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/platform/default/logging.h
CVE ID: CVE-2022-29210 State: PUBLISHED Published: 2022-05-20T23:25:21.000Z Last Updated: 2025-04-23T18:23:44.004Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-120, CWE-122 Description: TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function used total estimated `AllocatedBytes()`, which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. `int32_t`). It also tried to access individual tensor bytes through `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate
ough `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the `.data()` buffer. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/release
ences: - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hc2f-7r5r-r2hg - https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/framework/tensor_key.h#L53-L64
CVE ID: CVE-2022-29211 State: PUBLISHED Published: 2022-05-20T23:20:15.000Z Last Updated: 2025-04-22T17:57:17.184Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the di
ined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/a
8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xrp2-fhq4-4q3w - https://github.com/tensorflow/tensorflow/issues/45770 - https://github.com/tensorflow/tensorflow/commit/e57fd691c7b0fd00ea3bfe43444f30c1969748b5 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74
CVE ID: CVE-2022-29212 State: PUBLISHED Published: 2022-05-20T23:15:15.000Z Last Updated: 2025-04-22T17:57:26.021Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TF
t code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8wwm-6264-x792 - https://github.com/te
es/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8wwm-6264-x792 - https://github.com/tensorflow/tensorflow/issues/43661 - https://github.com/tensorflow/tensorflow/commit/a989426ee1346693cc015792f11d715f6944f2b8 - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/lite/kernels/internal/quantization_util.cc#L114-L123
CVE ID: CVE-2022-29213 State: PUBLISHED Published: 2022-05-20T23:30:15.000Z Last Updated: 2025-04-22T17:56:54.042Z Severity: MEDIUM (CVSS 5.5 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-20 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: -
ontain a patch for this issue. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5889-7v45-q28m - https://github.com/tensorflow/tensorflow/issues/55263 - https://github.com/tensorflow/tensorflow/pull/55274 - https://github.com/tensorflow/tensorflow/commit/0a8a781e597b18ead006d19b7d23d0a369e9ad73
CVE ID: CVE-2022-29214 State: PUBLISHED Published: 2022-05-20T23:45:11.000Z Last Updated: 2025-04-23T18:23:37.970Z Severity: MEDIUM (CVSS 6.1 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N) Vendors: nextauthjs Products: next-auth Problem Types: CWE-601 Description: NextAuth.js (next-auth) is am open source authentication solution for Next.js applications. Prior to versions 3.29.3 and 4.3.3, an open redirect vulnerability is present when the developer is implementing an OAuth 1 provider. Versions 3.29.3 and 4.3.3 contain a patch for this issue. The maintainers recommend adding a certain configuration to one's `callbacks` option as a workaround for those unable to upgrade. Additional Analyst Not
a certain configuration to one's `callbacks` option as a workaround for those unable to upgrade. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/nextauthjs/next-auth/security/advisories/GHSA-q2mx-j4x2-2h74 - https://github.com/nextauthjs/next-auth/releases/tag/next-auth%40v4.3.3
CVE ID: CVE-2022-29215 State: PUBLISHED Published: 2022-05-21T00:05:10.000Z Last Updated: 2025-04-23T18:23:03.290Z Severity: HIGH (CVSS 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H) Vendors: kaidomc-pm-pl Products: RegionProtect Problem Types: CWE-88 Description: RegionProtect is a plugin that allows users to manage certain events in certain regions of the world. Versions prior to 1.1.0 contain a YAML injection vulnerability that can cause an instant server crash if the passed arguments are not matched. Version 1.1.0 contains a patch for this issue. As a workaround, restrict operator permissions to untrusted people and avoid entering arguments likely to cause a crash. Additional Analyst
trict operator permissions to untrusted people and avoid entering arguments likely to cause a crash. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/kaidomc-pm-pl/RegionProtect/security/advisories/GHSA-7gr2-w2r3-r9vf - https://github.com/kaidomc-pm-pl/RegionProtect/commit/0060d421358ab59acb6a168eab0d11c43d2d105d
CVE ID: CVE-2022-29216 State: PUBLISHED Published: 2022-05-20T23:35:13.000Z Last Updated: 2025-04-22T17:56:38.650Z Severity: HIGH (CVSS 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H) Vendors: tensorflow Products: tensorflow Problem Types: CWE-94 Description: TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of th
es where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/tensorflow/tensorflow/commit/8b202f08d52e8206af2bdb2112a62fafbc546ec7 - https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4 - https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://gith
/tensorflow/tensorflow/releases/tag/v2.7.2 - https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1 - https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0 - https://github.com/tensorflow/tensorflow/security/advisories/GHSA-75c9-jrh4-79mc - https://github.com/tensorflow/tensorflow/commit/c5da7af048611aa29e9382371f0aed5018516cac - https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/tools/saved_model_cli.py#L566-L574
CVE ID: CVE-2022-29217 State: PUBLISHED Published: 2022-05-24T14:10:10.000Z Last Updated: 2025-04-23T18:22:46.326Z Severity: HIGH (CVSS 7.4 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:N) Vendors: jpadilla Products: pyjwt Problem Types: CWE-327 Description: PyJWT is a Python implementation of RFC 7519. PyJWT supports multiple different JWT signing algorithms. With JWT, an attacker submitting the JWT token can choose the used signing algorithm. The PyJWT library requires that the application chooses what algorithms are supported. The application can specify `jwt.algorithms.get_default_algorithms()` to get support for all algorithms, or specify a single algorithm. The issue is not that big as `a
_default_algorithms()` to get support for all algorithms, or specify a single algorithm. The issue is not that big as `algorithms=jwt.algorithms.get_default_algorithms()` has to be used. Users should upgrade to v2.4.0 to receive a patch for this issue. As a workaround, always be explicit with the algorithms that are accepted and expected when decoding. Additional Analyst Notes: - CVE Program Container: - CISA ADP Vulnrichment: References: - https://github.com/jpadilla/pyjwt/security/advisories/GHSA-ffqj-6fqr-9h24 - https://github.com/jpadilla/pyjwt/commit/9c528670c455b8d948aff95ed50e22940d1ad3fc - https://github.com/jpadilla/pyjwt/releases/tag/2.4.0 - https://lists.fedoraproject.org/archives
aff95ed50e22940d1ad3fc - https://github.com/jpadilla/pyjwt/releases/tag/2.4.0 - https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/6HIYEYZRQEP6QTHT3EHH3RGFYJIHIMAO/ - https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/5PK7IQCBVNLYJEFTPHBBPFP72H4WUFNX/
CVE ID: CVE-2022-29218 State: PUBLISHED Published: 2022-05-12T23:55:08.000Z Last Updated: 2025-04-22T18:01:45.416Z Severity: HIGH (CVSS 7.7 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:H/A:N) Vendors: rubygems Products: rubygems.org Problem Types: CWE-269, CWE-290 Description: RubyGems is a package registry used to supply software for the Ruby language ecosystem. An ordering mistake in the code that accepts gem uploads allowed some gems (with platforms ending in numbers, like `arm64-darwin-21`) to be temporarily replaced in the CDN cache by a malicious package. The bug has been patched, and is believed to have never been exploited, based on an extensive review of logs and existing gems by rubygems