CVE-2022-35985 json
`CHECK` fail in `LRNGrad` in TensorFlow
published 2022-09-16 4 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-35985 , EUVD-2022-6754 , GHSA-9942-r22v-78cp , PYSEC-2026-3147 , PYSEC-2026-3303 , PYSEC-2026-975
- cvss
- 5.9
- 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 41%
- public exploits
- 0
- none known
Summary
TensorFlow is an open source platform for machine learning. If `LRNGrad` is given an `output_image` input tensor that is not 4-D, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bd90b3efab4ec958b228cd7cfe9125be1c0cf255. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Patch / fix
- pypi tensorflow 2.7.2, 2.8.1, 2.9.1
- pypi tensorflow-cpu 2.7.2, 2.8.1, 2.9.1
- pypi tensorflow-gpu 2.7.2, 2.8.1, 2.9.1
- bitnami tensorflow 2.7.2, 2.8.1, 2.9.1
- google tensorflow 2.7.2, 2.8.1, 2.9.1
CISA SSVC
- Exploitation
- none
- Automatable
- no
- Technical impact
- partial
- Assessed
- 18 mo ago
Exploit prediction
0.48% chance of exploitation in the next 30 days, higher than 41% of all scored CVEs (FIRST EPSS, 2026-11-08).
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 5.9 | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 5.9 | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/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 | 5.9 | CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | <2.7.2 >=2.8.0, <2.8.1 >=2.9.0, <2.9.1 |
2.7.2 2.8.1 2.9.1 |
| pypi | tensorflow-cpu | <2.7.2 >=2.8.0, <2.8.1 >=2.9.0, <2.9.1 |
2.7.2 2.8.1 2.9.1 |
| pypi | tensorflow-gpu | <2.7.2 >=2.8.0, <2.8.1 >=2.9.0, <2.9.1 |
2.7.2 2.8.1 2.9.1 |
| bitnami | tensorflow | <2.7.2 >=2.8.0, <2.8.1 >=2.9.0, <2.9.1 |
2.7.2 2.8.1 2.9.1 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-617 Reachable Assertion
References
-
github.com
/tensorflow/tensorflow/commit/bd90b3efab4ec958b228cd7cfe9125be1c0cf255
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-9942-r22v-78cp
web, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-35985
advisory, web
-
github.com
/tensorflow/tensorflow
package
-
github.com
/tensorflow/tensorflow/releases/tag/v2.10.0
web
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-9942-r22v-78cp
advisory
-
pypi.org
/project/tensorflow-cpu
package
-
pypi.org
/project/tensorflow-gpu
package
Sources
- CVE List CVE-2022-35985
- GitHub Advisory GHSA-9942-r22v-78cp
- NVD CVE-2022-35985
- OSV BIT-tensorflow-2022-35985
- OSV PYSEC-2026-3147
- OSV PYSEC-2026-3303
- OSV PYSEC-2026-975
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.