CVE-2022-35974 json
Segfault in `QuantizeDownAndShrinkRange` in TensorFlow
published 4y ago modified 2mo ago also BIT-tensorflow-2022-35974 , EUVD-2022-6947 , GHSA-vgvh-2pf4-jr2x , PYSEC-2026-1039 , PYSEC-2026-3246 , PYSEC-2026-3373
- 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 43%
- public exploits
- 0
- none known
Summary
TensorFlow is an open source platform for machine learning. If `QuantizeDownAndShrinkRange` is given nonscalar inputs for `input_min` or `input_max`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 73ad1815ebcfeb7c051f9c2f7ab5024380ca8613. 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
Is CVE-2022-35974 in your dependencies? Fencer shows which of your repositories are affected as soon as an advisory lands, and opens the fix as a pull request.
Check with FencerCISA SSVC
- Exploitation
- none
- Automatable
- no
- Technical impact
- partial
- Assessed
- last yr.
Exploit prediction
0.51% chance of exploitation in the next 30 days, higher than 43% of all scored CVEs (FIRST EPSS, 2026-11-09).
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 | >=2.7.0, <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-20 Improper Input Validation
References
-
github.com
/tensorflow/tensorflow/commit/73ad1815ebcfeb7c051f9c2f7ab5024380ca8613
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-vgvh-2pf4-jr2x
web, patch, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-35974
advisory, web
-
github.com
/tensorflow/tensorflow
package
-
github.com
/tensorflow/tensorflow/releases/tag/v2.10.0
web
-
pypi.org
/project/tensorflow-gpu
package
-
github.com
/advisories/GHSA-vgvh-2pf4-jr2x
advisory
-
pypi.org
/project/tensorflow
package
-
pypi.org
/project/tensorflow-cpu
package
Sources
- CVE List CVE-2022-35974
- GitHub Advisory GHSA-vgvh-2pf4-jr2x
- NVD CVE-2022-35974
- OSV BIT-tensorflow-2022-35974
- OSV PYSEC-2026-1039
- OSV PYSEC-2026-3246
- OSV PYSEC-2026-3373
Fencer Intel 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.