Skip to content
Fencer Intel
low 2.5

CVE-2021-29569 json

Heap out of bounds read in `RequantizationRange`

published 5y ago modified 2mo ago also BIT-tensorflow-2021-29569 , EUVD-2021-0310 , GHSA-3h8m-483j-7xxm , PYSEC-2021-206 , PYSEC-2021-497 , PYSEC-2021-695

cvss
2.5
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.2%
EPSS 0.2% chance of exploitation in 30 days, percentile 9%
public exploits
0
none known

Summary

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs. The implementation(https://github.com/tensorflow/tensorflow/blob/ac328eaa3870491ababc147822cd04e91a790643/tensorflow/core/kernels/requantization_range_op.cc#L49-L50) assumes that the `input_min` and `input_max` tensors have at least one element, as it accesses the first element in two arrays. If the tensors are empty, `.flat<T>()` is an empty object, backed by an empty array. Hence, accesing even the 0th element is a read outside the bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Patch / fix

  • pypi tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
  • pypi tensorflow-cpu 2.1.4, 2.2.3, 2.3.3, 2.4.2
  • pypi tensorflow-gpu 2.1.4, 2.2.3, 2.3.3, 2.4.2
  • bitnami tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
  • google tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2
  • tensorflow Arch Linux 2.5.0-1

arch linux advisories AVG-1962

Is CVE-2021-29569 in your dependencies? Fencer shows which of your repositories are affected as soon as an advisory lands, and opens the fix as a pull request.

Check with Fencer

Exploit prediction

0.20% chance of exploitation in the next 30 days, higher than 9% of all scored CVEs (FIRST EPSS, 2026-11-09).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3h8m-483j-7xxm referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
GitHub 3.1 2.5 CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
NVD 3.1 7.1 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H
NVD 2.0 3.6 AV:L/AC:L/Au:N/C:P/I:N/A:P
OSV 3.1 7.1 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<2.1.4
>=2.2.0, <2.2.3
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
2.1.4
2.2.3
2.3.3
2.4.2
pypi tensorflow-cpu
<2.1.4
>=2.2.0, <2.2.3
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
2.1.4
2.2.3
2.3.3
2.4.2
pypi tensorflow-gpu
<2.1.4
>=2.2.0, <2.2.3
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
2.1.4
2.2.3
2.3.3
2.4.2
bitnami tensorflow
<2.1.4
>=2.2.0, <2.2.3
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
2.1.4
2.2.3
2.3.3
2.4.2

Affected products

  • tensorflow tensorflow

Classification

Weakness

References

Sources

Fencer Intel keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.