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Fencer Vulns
medium 4.4

CVE-2020-26271 json

Heap out of bounds access in MakeEdge in TensorFlow

published 2020-12-10 5 y ago modified 2026-09-10 1 mo ago also BIT-tensorflow-2020-26271 , EUVD-2020-0218 , GHSA-q263-fvxm-m5mw , PYSEC-2020-257 , PYSEC-2020-302 , PYSEC-2020-337

cvss
4.4
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 12%
public exploits
0
none known

Summary

In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

Patch / fix

  • pypi tensorflow 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  • pypi tensorflow-cpu 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  • pypi tensorflow-gpu 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  • bitnami tensorflow 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  • google tensorflow 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2
  • tensorflow2 Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • bazel3.7 Package Hub 15 SP3, openSUSE Leap 15.3 3.7.2-bp153.4.1
  • tensorflow2-lite Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • bazel-skylib1.0.3 Package Hub 15 SP3, openSUSE Leap 15.3 1.0.3-bp153.2.1
  • tensorflow2_2_6_0-gnu-hpc Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1
  • tensorflow2_2_6_0-gnu-openmpi2-hpc Package Hub 15 SP3, openSUSE Leap 15.3 2.6.0-bp153.2.3.1

opensuse advisories openSUSE-SU-2022:10014-1

  • tensorflow Arch Linux 2.4.0-1

arch linux advisories AVG-1348

Exploit prediction

0.22% chance of exploitation in the next 30 days, higher than 12% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 4.4 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
GitHub 3.1 4.4 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L
NVD 3.1 3.3 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
NVD 2.0 2.1 AV:L/AC:L/Au:N/C:P/I:N/A:N
OSV 3.1 4.4 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<1.15.5
>=2.0.0, <2.0.4
>=2.1.0, <2.1.3
>=2.2.0, <2.2.2
>=2.3.0, <2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
pypi tensorflow-cpu
<1.15.5
>=2.0.0, <2.0.4
>=2.1.0, <2.1.3
>=2.2.0, <2.2.2
>=2.3.0, <2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
pypi tensorflow-gpu
<1.15.5
>=2.0.0, <2.0.4
>=2.1.0, <2.1.3
>=2.2.0, <2.2.2
>=2.3.0, <2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
bitnami tensorflow
<1.15.5
>=2.0.0, <2.0.4
>=2.1.0, <2.1.3
>=2.2.0, <2.2.2
>=2.3.0, <2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2

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.