Vulnerability in Google Tensorflow
CVE-2022-41887
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.
EPSS: 0.004 (36.1th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 4.8 (Medium). Vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.10.0
- Tensorflow — versions >= 2.10.0, < 2.10.1, < 2.9.3
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (Exploit, Patch, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory)
- security-advisories@github.com (Third Party Advisory)
- security-advisories@github.com (Third Party Advisory)
Frequently asked questions
- What is CVE-2022-41887?
- CVE-2022-41887 is a medium-severity vulnerability in Google Tensorflow, classified under Incorrect Calculation of Buffer Size. CVSS score: 4.8/10. Published 2022-11-18.
- How severe is CVE-2022-41887?
- Medium severity. CVSS v3 base score is 4.8 out of 10.
- Is CVE-2022-41887 known to be exploited?
- 2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.