pysec-2021-212
Vulnerability from pysec
TensorFlow is an end-to-end open source platform for machine learning. The implementation of tf.raw_ops.ReverseSequence
allows for stack overflow and/or CHECK
-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that seq_dim
and batch_dim
arguments are valid. Negative values for seq_dim
can result in stack overflow or CHECK
-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of batch_dim
. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow", "purl": "pkg:pypi/tensorflow" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "ecf768cbe50cedc0a45ce1ee223146a3d3d26d23" } ], "repo": "https://github.com/tensorflow/tensorflow", "type": "GIT" }, { "events": [ { "introduced": "0" }, { "fixed": "2.2.0rc0" }, { "introduced": "2.2.0" }, { "fixed": "2.2.3" }, { "introduced": "2.3.0" }, { "fixed": "2.3.3" }, { "introduced": "2.4.0" }, { "fixed": "2.4.2" } ], "type": "ECOSYSTEM" } ], "versions": [ "0.12.0", "0.12.0rc0", "0.12.0rc1", "0.12.1", "1.0.0", "1.0.1", "1.1.0", "1.1.0rc0", "1.1.0rc1", "1.1.0rc2", "1.10.0", "1.10.0rc0", "1.10.0rc1", "1.10.1", "1.11.0", "1.11.0rc0", "1.11.0rc1", "1.11.0rc2", "1.12.0", "1.12.0rc0", "1.12.0rc1", "1.12.0rc2", "1.12.2", "1.12.3", "1.13.0rc0", "1.13.0rc1", "1.13.0rc2", "1.13.1", "1.13.2", "1.14.0", "1.14.0rc0", "1.14.0rc1", "1.15.0", "1.15.0rc0", "1.15.0rc1", "1.15.0rc2", "1.15.0rc3", "1.15.2", "1.15.3", "1.15.4", "1.15.5", "1.2.0", "1.2.0rc0", "1.2.0rc1", "1.2.0rc2", "1.2.1", "1.3.0", "1.3.0rc0", "1.3.0rc1", "1.3.0rc2", "1.4.0", "1.4.0rc0", "1.4.0rc1", "1.4.1", "1.5.0", "1.5.0rc0", "1.5.0rc1", "1.5.1", "1.6.0", "1.6.0rc0", "1.6.0rc1", "1.7.0", "1.7.0rc0", "1.7.0rc1", "1.7.1", "1.8.0", "1.8.0rc0", "1.8.0rc1", "1.9.0", "1.9.0rc0", "1.9.0rc1", "1.9.0rc2", "2.0.0", "2.0.0a0", "2.0.0b0", "2.0.0b1", "2.0.0rc0", "2.0.0rc1", "2.0.0rc2", "2.0.1", "2.0.2", "2.0.3", "2.0.4", "2.1.0", "2.1.0rc0", "2.1.0rc1", "2.1.0rc2", "2.1.1", "2.1.2", "2.1.3", "2.1.4", "2.2.0", "2.2.1", "2.2.2", "2.3.0", "2.3.1", "2.3.2", "2.4.0", "2.4.1" ] } ], "aliases": [ "CVE-2021-29575", "GHSA-6qgm-fv6v-rfpv" ], "details": "TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service. The implementation(https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid. Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.", "id": "PYSEC-2021-212", "modified": "2021-08-27T03:22:34.716646Z", "published": "2021-05-14T20:15:00Z", "references": [ { "type": "ADVISORY", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6qgm-fv6v-rfpv" }, { "type": "FIX", "url": "https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23" } ] }
Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.