CVE-2022-23580 json
Abort caused by allocating a vector that is too large in Tensorflow
published 2022-02-04 4 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-23580 , EUVD-2022-0328 , GHSA-627q-g293-49q7 , PYSEC-2022-144 , PYSEC-2022-89 , PYSEC-2026-3113
- 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 57%
- public exploits
- 0
- none known
Summary
Tensorflow is an Open Source Machine Learning Framework. During shape inference, TensorFlow can allocate a large vector based on a value from a tensor controlled by the user. 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
CISA SSVC
- Exploitation
- Proof of concept is public
- Automatable
- no
- Technical impact
- partial
- Assessed
- 18 mo ago
Exploit prediction
0.83% chance of exploitation in the next 30 days, higher than 57% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L788-L790 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 | 5.0 | AV:N/AC:L/Au:N/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 |
Affected products
- tensorflow tensorflow
Classification
References
-
github.com
/tensorflow/tensorflow/commit/1361fb7e29449629e1df94d44e0427ebec8c83c7
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-627q-g293-49q7
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference
web, exploit, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-23580
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-89.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-144.yaml
web
-
github.com
/tensorflow/tensorflow
web
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-627q-g293-49q7
advisory
Sources
- CVE List CVE-2022-23580
- GitHub Advisory GHSA-627q-g293-49q7
- NVD CVE-2022-23580
- OSV BIT-tensorflow-2022-23580
- OSV PYSEC-2022-144
- OSV PYSEC-2022-89
- OSV PYSEC-2026-3113
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.