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Fencer Vulns
critical 9.0

CVE-2020-15202 json

Integer truncation in Shard API usage

published 2020-09-25 6 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2020-15202 , EUVD-2020-0198 , GHSA-h6fg-mjxg-hqq4 , PYSEC-2020-125 , PYSEC-2020-282 , PYSEC-2020-317

cvss
9.0
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
1.3%
EPSS 1.3% chance of exploitation in 30 days, percentile 70%
public exploits
0
none known

Summary

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `Shard` API in TensorFlow expects the last argument to be a function taking two `int64` (i.e., `long long`) arguments. However, there are several places in TensorFlow where a lambda taking `int` or `int32` arguments is being used. In these cases, if the amount of work to be parallelized is large enough, integer truncation occurs. Depending on how the two arguments of the lambda are used, this can result in segfaults, read/write outside of heap allocated arrays, stack overflows, or data corruption. The issue is patched in commits 27b417360cbd671ef55915e4bb6bb06af8b8a832 and ca8c013b5e97b1373b3bb1c97ea655e69f31a575, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Patch / fix

  • pypi tensorflow 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  • pypi tensorflow-cpu 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  • pypi tensorflow-gpu 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  • bitnami tensorflow 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  • google tensorflow 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1
  • tensorflow2 openSUSE Leap 15.2 2.1.2-lp152.7.3.1
  • tensorflow2-lite openSUSE Leap 15.2 2.1.2-lp152.7.3.1
  • tensorflow2_2_1_2-gnu-hpc openSUSE Leap 15.2 2.1.2-lp152.7.3.1
  • tensorflow2_2_1_2-gnu-openmpi2-hpc openSUSE Leap 15.2 2.1.2-lp152.7.3.1

opensuse advisories openSUSE-SU-2020:1766-1

Exploit prediction

1.29% chance of exploitation in the next 30 days, higher than 70% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h6fg-mjxg-hqq4 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 9.0 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
GitHub 3.1 9.0 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
NVD 3.1 9.0 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
NVD 2.0 6.8 AV:N/AC:M/Au:N/C:P/I:P/A:P
OSV 3.1 9.0 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<1.15.4
>=2.0.0, <2.0.3
>=2.1.0, <2.1.2
>=2.2.0, <2.2.1
>=2.3.0, <2.3.1
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1
pypi tensorflow-cpu
<1.15.4
>=2.0.0, <2.0.3
>=2.1.0, <2.1.2
>=2.2.0, <2.2.1
>=2.3.0, <2.3.1
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1
pypi tensorflow-gpu
<1.15.4
>=2.0.0, <2.0.3
>=2.1.0, <2.1.2
>=2.2.0, <2.2.1
>=2.3.0, <2.3.1
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1
bitnami tensorflow
<1.15.4
>=2.0.0, <2.0.3
>=2.1.0, <2.1.2
>=2.2.0, <2.2.1
>=2.3.0, <2.3.1
1.15.4
2.0.3
2.1.2
2.2.1
2.3.1

Affected products

  • tensorflow tensorflow

Classification

Weakness
  • CWE-197 Numeric Truncation Error
  • CWE-754 Improper Check for Unusual or Exceptional Conditions

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.