Skip to content
Fencer Vulns
medium 4.3

CVE-2022-23585 json

Memory leak in decoding PNG images in Tensorflow

published 2022-02-04 4 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-23585 , EUVD-2022-0333 , GHSA-fq6p-6334-8gr4 , PYSEC-2022-149 , PYSEC-2022-94 , PYSEC-2026-3174

cvss
4.3
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
1.0%
EPSS 1.0% chance of exploitation in 30 days, percentile 63%
public exploits
0
none known

Summary

Tensorflow is an Open Source Machine Learning Framework. When decoding PNG images TensorFlow can produce a memory leak if the image is invalid. After calling `png::CommonInitDecode(..., &decode)`, the `decode` value contains allocated buffers which can only be freed by calling `png::CommonFreeDecode(&decode)`. However, several error case in the function implementation invoke the `OP_REQUIRES` macro which immediately terminates the execution of the function, without allowing for the memory free to occur. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Patch / fix

  • pypi tensorflow 2.5.3, 2.6.3, 2.7.1
  • pypi tensorflow-cpu 2.5.3, 2.6.3, 2.7.1
  • pypi tensorflow-gpu 2.5.3, 2.6.3, 2.7.1
  • bitnami tensorflow 2.5.3, 2.6.3, 2.7.1

CISA SSVC

Exploitation
Proof of concept is public
Automatable
no
Technical impact
partial
Assessed
18 mo ago

Exploit prediction

1.00% chance of exploitation in the next 30 days, higher than 63% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/kernels/image/decode_image_op.cc#L322-L416 referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
GitHub 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
NVD 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 2.0 4.0 AV:N/AC:L/Au:S/C:N/I:N/A:P
OSV 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
OSV 3.1 4.3 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L

Affected packages

ecosystem package affected fixed in
pypi tensorflow
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
pypi tensorflow-cpu
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
pypi tensorflow-gpu
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1
bitnami tensorflow
<2.5.3
>=2.6.0, <2.6.3
>=2.7.0, <2.7.1
2.5.3
2.6.3
2.7.1

Affected products

  • tensorflow tensorflow

Classification

Weakness
  • CWE-401 Missing Release of Memory after Effective Lifetime

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.