CVE-2022-23557 json
Division by zero in TFLite
published 2022-02-04 4 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2022-23557 , EUVD-2022-0305 , GHSA-gf2j-f278-xh4v , PYSEC-2022-121 , PYSEC-2022-66 , PYSEC-2026-3188
- 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 55%
- public exploits
- 0
- none known
Summary
Tensorflow is an Open Source Machine Learning Framework. An attacker can craft a TFLite model that would trigger a division by zero in `BiasAndClamp` implementation. There is no check that the `bias_size` is non zero. 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
0.76% chance of exploitation in the next 30 days, higher than 55% of all scored CVEs (FIRST EPSS, 2026-11-08).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75 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 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-369 Divide By Zero
References
-
github.com
/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h
web, exploit, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-23557
advisory, web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-66.yaml
web
-
github.com
/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-121.yaml
web
-
github.com
/tensorflow/tensorflow
web
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-gf2j-f278-xh4v
advisory
Sources
- CVE List CVE-2022-23557
- GitHub Advisory GHSA-gf2j-f278-xh4v
- NVD CVE-2022-23557
- OSV BIT-tensorflow-2022-23557
- OSV PYSEC-2022-121
- OSV PYSEC-2022-66
- OSV PYSEC-2026-3188
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.