CVE-2022-41901 json
`CHECK_EQ` fail via input in `SparseMatrixNNZ` in Tensorflow
published 2022-11-18 3 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-41901 , EUVD-2022-7345 , GHSA-g9fm-r5mm-rf9f , PYSEC-2026-3185 , PYSEC-2026-3328 , PYSEC-2026-997
- cvss
- 4.8
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.5%
- EPSS 0.5% chance of exploitation in 30 days, percentile 42%
- public exploits
- 0
- none known
Summary
TensorFlow is an open source platform for machine learning. An input `sparse_matrix` that is not a matrix with a shape with rank 0 will trigger a `CHECK` fail in `tf.raw_ops.SparseMatrixNNZ`. We have patched the issue in GitHub commit f856d02e5322821aad155dad9b3acab1e9f5d693. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
Patch / fix
- pypi tensorflow 2.8.4, 2.9.3, 2.10.1
- pypi tensorflow-cpu 2.8.4, 2.9.3, 2.10.1
- pypi tensorflow-gpu 2.8.4, 2.9.3, 2.10.1
- bitnami tensorflow 2.8.4, 2.9.3, 2.10.1
- google tensorflow 2.8.4, 2.9.3, 2.10.1
CISA SSVC
- Exploitation
- Proof of concept is public
- Automatable
- no
- Technical impact
- partial
- Assessed
- 18 mo ago
Exploit prediction
0.49% chance of exploitation in the next 30 days, higher than 42% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g9fm-r5mm-rf9f referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H |
| NVD | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| OSV | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| OSV | 3.1 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | <2.8.4 >=2.9.0, <2.9.3 >=2.10.0, <2.10.1 |
2.8.4 2.9.3 2.10.1 |
| pypi | tensorflow-cpu | <2.8.4 >=2.9.0, <2.9.3 >=2.10.0, <2.10.1 |
2.8.4 2.9.3 2.10.1 |
| pypi | tensorflow-gpu | <2.8.4 >=2.9.0, <2.9.3 >=2.10.0, <2.10.1 |
2.8.4 2.9.3 2.10.1 |
| bitnami | tensorflow | <2.8.4 >=2.9.0, <2.9.3 >=2.10.0, <2.10.1 |
2.8.4 2.9.3 2.10.1 |
Affected products
- tensorflow tensorflow
Classification
References
-
github.com
/tensorflow/tensorflow/commit/f856d02e5322821aad155dad9b3acab1e9f5d693
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-g9fm-r5mm-rf9f
web, exploit, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/sparse/sparse_matrix.h
web, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-41901
advisory, web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-g9fm-r5mm-rf9f
advisory
-
pypi.org
/project/tensorflow-cpu
package
-
pypi.org
/project/tensorflow-gpu
package
Sources
- CVE List CVE-2022-41901
- GitHub Advisory GHSA-g9fm-r5mm-rf9f
- NVD CVE-2022-41901
- OSV BIT-tensorflow-2022-41901
- OSV PYSEC-2026-3185
- OSV PYSEC-2026-3328
- OSV PYSEC-2026-997
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.