Buffer overflow in Google Tensorflow
CVE-2021-41216
TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Vulnerability class: Buffer Overflow
EPSS: 0.002 (5.3th percentile) — read the EPSS interpretation.
CVSS v3 metric
CVSS v3 base score 5.5 (Medium). Vector: CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
Affected products
- Google Tensorflow — versions 2.7.0
- Tensorflow — versions >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4
Weakness classification (CWE)
Public proof-of-concept exploits
References
- security-advisories@github.com (x_refsource_CONFIRM, Third Party Advisory)
- security-advisories@github.com (Patch, Third Party Advisory, x_refsource_MISC)
Frequently asked questions
- What is CVE-2021-41216?
- CVE-2021-41216 is a medium-severity vulnerability in Google Tensorflow, classified under Buffer Copy without Checking Size of Input (Classic Buffer Overflow). CVSS score: 5.5/10. Published 2021-11-05.
- How severe is CVE-2021-41216?
- Medium severity. CVSS v3 base score is 5.5 out of 10.
- Is CVE-2021-41216 known to be exploited?
- 2 public proof-of-concept repositories are indexed. Not currently listed in the CISA KEV catalog.