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GHSA-jq6x-99hj-q636 BIT-tensorflow-2022-41884 CVE-2022-41884 PYSEC-2026-1013 PYSEC-2026-3208 PYSEC-2026-3345

Seg fault in `ndarray_tensor_bridge` due to zero and large inputs

Medium PyPI
Severity
4.8 / 10
Medium · CVSS 3.1
Exploit chance (EPSS)
0.37%
Chance of exploitation in the next 30 days. Higher than 30.98% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-670 Always-Incorrect Control Flow Implementation
Fix
Available
3 packages have a fixed version

Description

Impact

If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:

np.ones((0, 2**31, 2**31))

An example of a proof of concept:

import numpy as np
import tensorflow as tf

input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])

tf.broadcast_to(input=input_val,shape=shape_val)

The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.

Patches

We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Pattarakrit Rattanukul.

Affected versions

PyPI

PackageVulnerableFixed in
tensorflow
< 2.8.4
2.8.4
tensorflow
>= 2.9.0, < 2.9.3
2.9.3
tensorflow
>= 2.10.0, < 2.10.1
2.10.1
tensorflow
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
2.8.4
2.9.3
2.10.1
tensorflow-cpu
< 2.8.4
2.8.4
tensorflow-cpu
>= 2.9.0, < 2.9.3
2.9.3
tensorflow-cpu
>= 2.10.0, < 2.10.1
2.10.1
tensorflow-cpu
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
2.8.4
2.9.3
2.10.1
tensorflow-gpu
< 2.8.4
2.8.4
tensorflow-gpu
>= 2.9.0, < 2.9.3
2.9.3
tensorflow-gpu
>= 2.10.0, < 2.10.1
2.10.1
tensorflow-gpu
< 2.8.4
>= 2.9.0, < 2.9.3
>= 2.10.0, < 2.10.1
2.8.4
2.9.3
2.10.1

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

tensorflow PyPI → 2.8.4

pip
pip install --upgrade "tensorflow>=2.8.4"
poetry
poetry add "tensorflow>=2.8.4"
uv
uv add "tensorflow>=2.8.4"

tensorflow-cpu PyPI → 2.8.4

pip
pip install --upgrade "tensorflow-cpu>=2.8.4"
poetry
poetry add "tensorflow-cpu>=2.8.4"
uv
uv add "tensorflow-cpu>=2.8.4"

tensorflow-gpu PyPI → 2.8.4

pip
pip install --upgrade "tensorflow-gpu>=2.8.4"
poetry
poetry add "tensorflow-gpu>=2.8.4"
uv
uv add "tensorflow-gpu>=2.8.4"

Severity breakdown

CVSS 3.1 4.8

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

Attack vector
Network
Attack complexity
High
Privileges required
Low
User interaction
Required
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-670: Always-Incorrect Control Flow Implementation

The code contains a control flow path that does not reflect the algorithm that the path is intended to implement, leading to incorrect behavior any time this path is navigated.

References

Advisories

Packages

Other links

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-gjh7-xx4r-x345
TensorFlow has segfault in array_ops.upper_bound
High Also affects tensorflow
GHSA-fxgc-95xx-grvq
TensorFlow Denial of Service vulnerability
Medium Also affects tensorflow
GHSA-93vr-9q9m-pj8p
TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch
High Also affects tensorflow
GHSA-qjqc-vqcf-5qvj
TensorFlow vulnerable to seg fault in `tf.raw_ops.Print`
High Also affects tensorflow
GHSA-7jvm-xxmr-v5cw
TensorFlow vulnerable to integer overflow in EditDistance
High Also affects tensorflow
GHSA-64jg-wjww-7c5w
TensorFlow has Null Pointer Error in TensorArrayConcatV2
High Also affects tensorflow
GHSA-6hg6-5c2q-7rcr
TensorFlow has Heap-buffer-overflow in AvgPoolGrad
High Also affects tensorflow
GHSA-558h-mq8x-7q9g
TensorFlow has Null Pointer Error in SparseSparseMaximum
High Also affects tensorflow
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