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CVE-2022-23576

MEDIUM
Published 2022-02-04T22:32:22.000Z
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CVSS Score

V3.1
6.5
/10
CVSS:3.1/AV:N/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
0.002
probability
of exploitation in the wild

There is a 0.2% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.435
Higher than 43.5% of all CVEs

Attack Vector Metrics

Attack Vector
NETWORK
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 Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateOutputSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements. We can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

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 HIGH

Integer overflow in Tensorflow

GHSA-wm93-f238-7v37

Advisory Details

### Impact The [implementation of `OpLevelCostEstimator::CalculateOutputSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1598-L1617) is vulnerable to an integer overflow if an attacker can create an operation which would involve tensors with large enough number of elements: ```cc for (const auto& dim : output_shape.dim()) { output_size *= dim.size(); } ``` Here, we can have a large enough number of dimensions in `output_shape.dim()` or just a small number of dimensions being large enough to cause an overflow in the multiplication. ### Patches We have patched the issue in GitHub commit [b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae](https://github.com/tensorflow/tensorflow/commit/b9bd6cfd1c50e6807846af9a86f9b83cafc9c8ae). The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. ### 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: ≥0 <2.5.3
PyPI tensorflow
ECOSYSTEM: ≥2.6.0 <2.6.3
PyPI tensorflow
ECOSYSTEM: ≥2.7.0 <2.7.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥0 <2.5.3
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.6.0 <2.6.3
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.7.0 <2.7.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥0 <2.5.3
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.6.0 <2.6.3
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.7.0 <2.7.1

CVSS Scoring

CVSS Score

7.5

CVSS Vector

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

Advisory provided by GitHub Security Advisory Database. Published: February 10, 2022, Modified: November 13, 2024

References

Published: 2022-02-04T22:32:22.000Z
Last Modified: 2025-04-22T18:25:25.949Z
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