CVE-2022-41887 json
Overflow in `tf.keras.losses.poisson` in Tensorflow
published 3y ago modified 2mo ago also BIT-tensorflow-2022-41887 , EUVD-2022-7281 , GHSA-8fvv-46hw-vpg3 , PYSEC-2026-3136 , PYSEC-2026-3297 , PYSEC-2026-970
- cvss
- 4.8
- 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 42%
- public exploits
- 0
- none known
Summary
TensorFlow is an open source platform for machine learning. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.
Patch / fix
- pypi tensorflow 2.9.3, 2.10.1
- pypi tensorflow-cpu 2.9.3, 2.10.1
- pypi tensorflow-gpu 2.9.3, 2.10.1
- bitnami tensorflow 2.9.3, 2.10.1
- google tensorflow 2.9.3
Is CVE-2022-41887 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
0.49% chance of exploitation in the next 30 days, higher than 42% of all scored CVEs (FIRST EPSS, 2026-11-09).
Exploits and checks
- github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8fvv-46hw-vpg3 referenced PoC, tagged "exploit" by a source, unverified
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/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 | 4.8 | CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | <2.9.3 >=2.10.0, <2.10.1 |
2.9.3 2.10.1 |
| pypi | tensorflow-cpu | <2.9.3 >=2.10.0, <2.10.1 |
2.9.3 2.10.1 |
| pypi | tensorflow-gpu | <2.9.3 >=2.10.0, <2.10.1 |
2.9.3 2.10.1 |
| bitnami | tensorflow | >=2.9.0, <2.9.3 >=2.10.0, <2.10.1 |
2.9.3 2.10.1 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-131 Incorrect Calculation of Buffer Size
References
-
github.com
/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c
web, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-8fvv-46hw-vpg3
web, exploit, patch, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h
web, third-party-advisory, advisory
-
github.com
/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py
web, third-party-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2022-41887
advisory, web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow
package
-
github.com
/advisories/GHSA-8fvv-46hw-vpg3
advisory
-
pypi.org
/project/tensorflow-cpu
package
-
pypi.org
/project/tensorflow-gpu
package
Sources
- CVE List CVE-2022-41887
- GitHub Advisory GHSA-8fvv-46hw-vpg3
- NVD CVE-2022-41887
- OSV BIT-tensorflow-2022-41887
- OSV PYSEC-2026-3136
- OSV PYSEC-2026-3297
- OSV PYSEC-2026-970
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.