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Fencer Vulns
low 2.5

CVE-2021-29514 json

Heap out of bounds write in `RaggedBinCount`

published 2021-05-14 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-29514 , EUVD-2021-0255 , GHSA-8h46-5m9h-7553 , PYSEC-2021-151 , PYSEC-2021-442 , PYSEC-2021-640

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 11%
public exploits
0
none known

Summary

TensorFlow is an end-to-end open source platform for machine learning. If the `splits` argument of `RaggedBincount` does not specify a valid `SparseTensor`(https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor), then an attacker can trigger a heap buffer overflow. This will cause a read from outside the bounds of the `splits` tensor buffer in the implementation of the `RaggedBincount` op(https://github.com/tensorflow/tensorflow/blob/8b677d79167799f71c42fd3fa074476e0295413a/tensorflow/core/kernels/bincount_op.cc#L430-L446). Before the `for` loop, `batch_idx` is set to 0. The attacker sets `splits(0)` to be 7, hence the `while` loop does not execute and `batch_idx` remains 0. This then results in writing to `out(-1, bin)`, which is before the heap allocated buffer for the output tensor. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2 and TensorFlow 2.3.3, as these are also affected.

Patch / fix

  • pypi tensorflow 2.2.0rc0, 2.3.0rc0, 2.3.3, 2.3.4, 2.4.2, 2.4.3
  • pypi tensorflow-cpu 2.2.0rc0, 2.3.0rc0, 2.3.3, 2.3.4, 2.4.2, 2.4.3
  • pypi tensorflow-gpu 2.2.0rc0, 2.3.0rc0, 2.3.3, 2.3.4, 2.4.2, 2.4.3
  • bitnami tensorflow 2.3.3, 2.4.2
  • google tensorflow 2.3.3, 2.4.2
  • tensorflow Arch Linux 2.5.0-1

arch linux advisories AVG-1962

Exploit prediction

0.21% chance of exploitation in the next 30 days, higher than 11% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8h46-5m9h-7553 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 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
NVD 2.0 4.6 AV:L/AC:L/Au:N/C:P/I:P/A:P
OSV 3.1 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
<2.2.0rc0
>=2.2.0, <2.3.0rc0
>=2.3.0, <2.3.4
>=2.4.0, <2.4.3
2.3.3
2.4.2
2.2.0rc0
2.3.0rc0
2.3.4
2.4.3
pypi tensorflow-cpu
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
<2.2.0rc0
>=2.2.0, <2.3.0rc0
>=2.3.0, <2.3.4
>=2.4.0, <2.4.3
2.3.3
2.4.2
2.2.0rc0
2.3.0rc0
2.3.4
2.4.3
pypi tensorflow-gpu
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
<2.2.0rc0
>=2.2.0, <2.3.0rc0
>=2.3.0, <2.3.4
>=2.4.0, <2.4.3
2.3.3
2.4.2
2.2.0rc0
2.3.0rc0
2.3.4
2.4.3
bitnami tensorflow
>=2.3.0, <2.3.3
>=2.4.0, <2.4.2
2.3.3
2.4.2

Affected products

  • tensorflow tensorflow

Classification

Weakness

References

Sources

Fencer Vulns 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.