Null pointer dereference in TensorFlow Lite MLIR optimizations
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 2.5.1, 2.4.3, 2.3.4
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The implementation unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Timeline
- CVE published
- Record last updated
Affected versions
- tensorflow tensorflow
From 2.5.0 · fixed in 2.5.1; From 2.4.0 · fixed in 2.4.3; fixed in 2.3.4
- tensorflowPyPI
fixed in 2.3.4
- tensorflowPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflowPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-cpuPyPI
fixed in 2.3.4
- tensorflow-cpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflow-gpuPyPI
fixed in 2.3.4
- tensorflow-gpuPyPI
From 2.4.0 · fixed in 2.4.3
- tensorflow-gpuPyPI
From 2.5.0 · fixed in 2.5.1
- tensorflowPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflow-cpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3
- tensorflow-gpuPyPI
From 2.3.0 · fixed in 2.3.4; From 2.4.0 · fixed in 2.4.3