pysec-2020-305
Vulnerability from pysec
In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch
operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr
, hence we are binding a reference to nullptr
. This is undefined behavior and reported as an error if compiling with -fsanitize=null
. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu", "purl": "pkg:pypi/tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "da8558533d925694483d2c136a9220d6d49d843c" } ], "repo": "https://github.com/tensorflow/tensorflow", "type": "GIT" }, { "events": [ { "introduced": "0" }, { "fixed": "1.15.4" }, { "introduced": "2.0.0" }, { "fixed": "2.0.3" }, { "introduced": "2.1.0" }, { "fixed": "2.1.2" }, { "introduced": "2.2.0" }, { "fixed": "2.2.1" }, { "introduced": "2.3.0" }, { "fixed": "2.3.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "0.12.0", "0.12.1", "1.0.0", "1.0.1", "1.1.0", "1.10.0", "1.10.1", "1.11.0", "1.12.0", "1.12.2", "1.12.3", "1.13.1", "1.13.2", "1.14.0", "1.15.0", "1.15.2", "1.15.3", "1.2.0", "1.2.1", "1.3.0", "1.4.0", "1.4.1", "1.5.0", "1.5.1", "1.6.0", "1.7.0", "1.7.1", "1.8.0", "1.9.0", "2.0.0", "2.0.1", "2.0.2", "2.1.0", "2.1.1", "2.2.0", "2.3.0" ] } ], "aliases": [ "CVE-2020-15190", "GHSA-4g9f-63rx-5cw4" ], "details": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.", "id": "PYSEC-2020-305", "modified": "2021-12-09T06:35:12.169887Z", "published": "2020-09-25T19:15:00Z", "references": [ { "type": "FIX", "url": "https://github.com/tensorflow/tensorflow/commit/da8558533d925694483d2c136a9220d6d49d843c" }, { "type": "ADVISORY", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4g9f-63rx-5cw4" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1" }, { "type": "WEB", "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html" } ] }
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.