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Security Advisories: GSA_kwCzR0hTQS1oYzJmLTdyNXItcjJoZ84AArBW

Heap buffer overflow due to incorrect hash function in TensorFlow

Impact

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 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. We couldn't use this byte vector anyways, since types like tstring include pointers, whereas we need to hash the string values themselves.

Patches

We have patched the issue in GitHub commit 1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, which is the only other affected version.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Permalink: https://github.com/advisories/GHSA-hc2f-7r5r-r2hg
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1oYzJmLTdyNXItcjJoZ84AArBW
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: almost 2 years ago
Updated: 9 months ago


CVSS Score: 5.5
CVSS vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Identifiers: GHSA-hc2f-7r5r-r2hg, CVE-2022-29210
References: Repository: https://github.com/tensorflow/tensorflow

Affected Packages

pypi:tensorflow-gpu
Dependent packages: 146
Dependent repositories: 11,499
Downloads: 354,170 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1
Fixed in: 2.8.1
All affected versions: 2.8.0
All unaffected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 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, 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, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 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, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71
Dependent repositories: 2,483
Downloads: 1,005,140 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1
Fixed in: 2.8.1
All affected versions: 2.8.0
All unaffected versions: 1.15.0, 2.1.0, 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, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733
Dependent repositories: 73,755
Downloads: 21,673,933 last month
Affected Version Ranges: >= 2.8.0, < 2.8.1
Fixed in: 2.8.1
All affected versions: 2.8.0
All unaffected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 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, 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, 1.15.4, 1.15.5, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0, 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, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1