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CVE-2022-29210

MEDIUM
Published 2022-05-20T23:25:21.000Z
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CVSS Score

V3.1
5.5
/10
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.001
probability
of exploitation in the wild

There is a 0.1% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.285
Higher than 28.5% of all CVEs

Attack Vector Metrics

Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
LOW
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
NONE
Integrity
NONE
Availability
HIGH

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 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.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed MODERATE

Heap buffer overflow due to incorrect hash function in TensorFlow

GHSA-hc2f-7r5r-r2hg

Advisory Details

### Impact The [`TensorKey` hash function](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/framework/tensor_key.h#L53-L64) 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](https://github.com/tensorflow/tensorflow/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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

Affected Packages

PyPI tensorflow
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.8.0 <2.8.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.8.0 <2.8.1

CVSS Scoring

CVSS Score

5.0

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: May 24, 2022, Modified: June 6, 2022

References

Published: 2022-05-20T23:25:21.000Z
Last Modified: 2025-04-23T18:23:44.004Z
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