CVE-2022-35973: TensorFlow is an open source platform for machine learning. If `QuantizedMatMul` is given nonscalar input for: `min_a`,
Summary
TensorFlow, an open source machine learning platform, has a vulnerability in its `QuantizedMatMul` function that crashes when given certain types of improper input (nonscalar values for min/max parameters), allowing attackers to trigger a denial of service attack (making the system unavailable). The issue has been fixed and will be released in updated versions of TensorFlow.
Solution / Mitigation
The fix is available in GitHub commit aca766ac7693bf29ed0df55ad6bfcc78f35e7f48 and will be included in TensorFlow 2.10.0. Users of TensorFlow 2.9.1, 2.8.1, and 2.7.2 should update to the patched versions of those releases (2.9.1, 2.8.1, and 2.7.2 respectively), as the fix will be cherry-picked into these supported versions.
Vulnerability Details
5.9(medium)
EPSS: 0.1%
Classification
Taxonomy References
Affected Vendors
Related Issues
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CVE-2021-29541: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a dereference of a null p
Original source: https://nvd.nist.gov/vuln/detail/CVE-2022-35973
First tracked: February 15, 2026 at 08:41 PM
Classified by LLM (prompt v3) · confidence: 95%