CVE-2022-21730 json
Out of bounds read in Tensorflow
published 4y ago modified last mo. also BIT-tensorflow-2022-21730 , EUVD-2022-0293 , GHSA-vjg4-v33c-ggc4 , PYSEC-2022-109 , PYSEC-2022-54 , PYSEC-2026-3247
- cvss
- 8.1
- 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 57%
- public exploits
- 0
- none known
Summary
Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalAvgPoolGrad` does not consider cases where the input tensors are invalid allowing an attacker to read from outside of bounds of heap. 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-2022-21730 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
0.82% chance of exploitation in the next 30 days, higher than 57% 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_avg_pool_op.cc#L209-L360 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 8.1 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H |
| GitHub | 3.1 | 8.1 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H |
| NVD | 3.1 | 8.1 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H |
| NVD | 2.0 | 5.5 | AV:N/AC:L/Au:S/C:P/I:N/A:P |
| OSV | 3.1 | 8.1 | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/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-125 Out-of-bounds Read
References
-
github.com
/tensorflow/tensorflow/commit/002408c3696b173863228223d535f9de72a101a9
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-vjg4-v33c-ggc4
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_avg_po
web, exploit, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-21730
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-54.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-109.yaml
web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-vjg4-v33c-ggc4
advisory
Sources
- CVE List CVE-2022-21730
- GitHub Advisory GHSA-vjg4-v33c-ggc4
- NVD CVE-2022-21730
- OSV BIT-tensorflow-2022-21730
- OSV PYSEC-2022-109
- OSV PYSEC-2022-54
- OSV PYSEC-2026-3247
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.