CVE-2022-21735 json
Division by zero in Tensorflow
published 4y ago modified last mo. also BIT-tensorflow-2022-21735 , EUVD-2022-0298 , GHSA-87v6-crgm-2gfj , PYSEC-2022-114 , PYSEC-2022-59 , PYSEC-2026-3134
- cvss
- 6.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.8%
- EPSS 0.8% chance of exploitation in 30 days, percentile 56%
- public exploits
- 0
- none known
Summary
Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. 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
Is CVE-2022-21735 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
- Proof of concept is public
- Automatable
- no
- Technical impact
- partial
- Assessed
- last yr.
Exploit prediction
0.79% chance of exploitation in the next 30 days, higher than 56% of all scored CVEs (FIRST EPSS, 2026-11-09).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 6.5 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| 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 |
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 |
Classification
- Weakness
-
- CWE-369 Divide By Zero
References
-
github.com
/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-87v6-crgm-2gfj
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_po
web, exploit, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-21735
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-59.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-114.yaml
web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-87v6-crgm-2gfj
advisory
Sources
- CVE List CVE-2022-21735
- GitHub Advisory GHSA-87v6-crgm-2gfj
- NVD CVE-2022-21735
- OSV BIT-tensorflow-2022-21735
- OSV PYSEC-2022-114
- OSV PYSEC-2022-59
- OSV PYSEC-2026-3134
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.