pysec-2021-189
Vulnerability from pysec
TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by controlling the values of num_segments
tensor argument for UnsortedSegmentJoin
. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a2a607db15c7cd01d754d37e5448d72a13491bdb/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L93) assumes that the num_segments
tensor is a valid scalar. Since the tensor is empty the CHECK
involved in .scalar<T>()()
that checks that the number of elements is exactly 1 will be invalidated and this would result in process termination. 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": "704866eabe03a9aeda044ec91a8d0c83fc1ebdbe" } ], "repo": "https://github.com/tensorflow/tensorflow", "type": "GIT" }, { "events": [ { "introduced": "0" }, { "fixed": "2.2.0rc0" }, { "introduced": "2.2.0" }, { "fixed": "2.3.0rc0" }, { "introduced": "2.3.0" }, { "fixed": "2.3.4" }, { "introduced": "2.4.0" }, { "fixed": "2.4.3" } ], "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", "2.2.3", "2.3.0", "2.3.1", "2.3.2", "2.3.3", "2.4.0", "2.4.1", "2.4.2" ] } ], "aliases": [ "CVE-2021-29552", "GHSA-jhq9-wm9m-cf89" ], "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by controlling the values of `num_segments` tensor argument for `UnsortedSegmentJoin`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a2a607db15c7cd01d754d37e5448d72a13491bdb/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L93) assumes that the `num_segments` tensor is a valid scalar. Since the tensor is empty the `CHECK` involved in `.scalar\u003cT\u003e()()` that checks that the number of elements is exactly 1 will be invalidated and this would result in process termination. 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-2021-189", "modified": "2021-08-27T03:22:30.663551Z", "published": "2021-05-14T20:15:00Z", "references": [ { "type": "ADVISORY", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jhq9-wm9m-cf89" }, { "type": "FIX", "url": "https://github.com/tensorflow/tensorflow/commit/704866eabe03a9aeda044ec91a8d0c83fc1ebdbe" } ] }
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.