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GSA_kwCzR0hTQS1ycngyLXI5ODktMmM0M80ohg

High CVSS: 7.1 EPSS: 0.0045% (0.62703 Percentile) EPSS:
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Integer overflows in Tensorflow

Affected Packages Affected Versions Fixed Versions
pypi:tensorflow-gpu
PURL: pkg:pypi/tensorflow-gpu
= 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3 2.7.1, 2.6.3, 2.5.3
155 Dependent packages
11,499 Dependent repositories
78,758 Downloads last month

Affected Version Ranges

All affected 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, 2.6.0, 2.6.1, 2.6.2, 2.7.0

All unaffected versions

2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 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
PURL: pkg:pypi/tensorflow-cpu
= 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3 2.7.1, 2.6.3, 2.5.3
88 Dependent packages
2,483 Dependent repositories
909,001 Downloads last month

Affected Version Ranges

All affected 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, 2.6.0, 2.6.1, 2.6.2, 2.7.0

All unaffected versions

2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0, 2.18.1, 2.19.0, 2.19.1, 2.20.0
pypi:tensorflow
PURL: pkg:pypi/tensorflow
= 2.7.0, >= 2.6.0, < 2.6.3, < 2.5.3 2.7.1, 2.6.3, 2.5.3
2,172 Dependent packages
73,755 Dependent repositories
21,825,433 Downloads last month

Affected Version Ranges

All affected 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, 2.6.0, 2.6.1, 2.6.2, 2.7.0

All unaffected versions

2.5.3, 2.6.3, 2.6.4, 2.6.5, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0, 2.18.1, 2.19.0, 2.19.1

Impact

The implementations of Sparse*Cwise* ops are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or CHECK-fails when building new TensorShape objects (so, assert failures based denial of service):

import tensorflow as tf
import numpy as np

tf.raw_ops.SparseDenseCwiseDiv(
    sp_indices=np.array([[9]]),
    sp_values=np.array([5]),
    sp_shape=np.array([92233720368., 92233720368]),
    dense=np.array([4]))

We are missing some validation on the shapes of the input tensors as well as directly constructing a large TensorShape with user-provided dimensions. The latter is an instance of TFSA-2021-198 (CVE-2021-41197) and is easily fixed by replacing a call to TensorShape constructor with a call to BuildTensorShape static helper factory.

Patches

We have patched the issue in GitHub commits 1b54cadd19391b60b6fcccd8d076426f7221d5e8 and e952a89b7026b98fe8cbe626514a93ed68b7c510.

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

Attribution

This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.

References:

Identifiers

GHSA-rrx2-r989-2c43

CVE-2022-23567

Risk

Severity

High

CVSS

CVSS Score: 7.1

CVSS vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS

EPSS Percentage: 0.0045

EPSS Percentile: 0.62703

Classification

General

Source

GitHub Advisory Database

Origin

Unspecified

Repository

https://github.com/tensorflow/tensorflow

Date and time

Published

over 3 years ago

Updated

10 months ago

API

JSON