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Fencer Vulns
low 2.5

CVE-2021-29529 json

Heap buffer overflow caused by rounding

published 2021-05-14 5 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2021-29529 , EUVD-2021-0270 , GHSA-jfp7-4j67-8r3q , PYSEC-2021-166 , PYSEC-2021-457 , PYSEC-2021-655

cvss
2.5
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.3%
EPSS 0.3% chance of exploitation in 30 days, percentile 16%
public exploits
0
none known

Summary

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a heap buffer overflow in `tf.raw_ops.QuantizedResizeBilinear` by manipulating input values so that float rounding results in off-by-one error in accessing image elements. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L62-L66) computes two integers (representing the upper and lower bounds for interpolation) by ceiling and flooring a floating point value. For some values of `in`, `interpolation->upper[i]` might be smaller than `interpolation->lower[i]`. This is an issue if `interpolation->upper[i]` is capped at `in_size-1` as it means that `interpolation->lower[i]` points outside of the image. Then, in the interpolation code(https://github.com/tensorflow/tensorflow/blob/44b7f486c0143f68b56c34e2d01e146ee445134a/tensorflow/core/kernels/quantized_resize_bilinear_op.cc#L245-L264), this would result in heap buffer overflow. 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

Exploit prediction

0.25% chance of exploitation in the next 30 days, higher than 16% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-jfp7-4j67-8r3q 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
<2.1.4
>=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
  • CWE-131 Incorrect Calculation of Buffer Size
  • CWE-193 Off-by-one Error

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.