CVE-2022-35967: TensorFlow is an open source platform for machine learning. If `QuantizedAdd` is given `min_input` or `max_input` tensor
Summary
TensorFlow, an open source machine learning platform, has a vulnerability in its `QuantizedAdd` function (a tool for adding quantized numbers, which are rounded values used to save memory). If this function receives certain tensor inputs of nonzero rank (multi-dimensional arrays), it crashes the program, which can be exploited to cause a denial of service attack (making the system unavailable to legitimate users).
Solution / Mitigation
The issue is patched in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. The fix will be included in TensorFlow 2.10.0 and will be backported (applied to older supported versions) as TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2.
Vulnerability Details
5.9(medium)
EPSS: 0.1%
Classification
Taxonomy References
Affected Vendors
Related Issues
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Original source: https://nvd.nist.gov/vuln/detail/CVE-2022-35967
First tracked: February 15, 2026 at 08:41 PM
Classified by LLM (prompt v3) · confidence: 95%