TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.
References
Link | Resource |
---|---|
https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244 | Patch Third Party Advisory |
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c | Exploit Third Party Advisory |
Configurations
History
No history.
Information
Published : 2021-11-05 21:15
Updated : 2021-11-09 15:14
NVD link : CVE-2021-41211
Mitre link : CVE-2021-41211
CVE.ORG link : CVE-2021-41211
JSON object : View
Products Affected
- tensorflow
CWE
CWE-125
Out-of-bounds Read