MediumVulnerability
CVE-2022-36005: TensorFlow denial of service via nonscalar min or max in fake_quant
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2022-36005
- Published
- Record updated
- Affected
- tensorflow < 2.7.2, fixed in 2.7.2, released May 16, 2022, 124 days before disclosure
- tensorflow >= 2.8.0, < 2.8.1, fixed in 2.8.1, released May 16, 2022, 124 days before disclosure
- tensorflow >= 2.9.0, < 2.9.1, fixed in 2.9.1, released May 23, 2022, 117 days before disclosure
- and 6 more
- Known exploitation
- Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
- EPSS
- 0.5%
Summary
TensorFlow's tf.quantization.fake_quant_with_min_max_vars_gradient triggers a CHECK failure when its min or max input is nonscalar, which can be exploited for a denial of service attack. The issue is tracked as CVE-2022-36005 and affects versions still in the supported range.
Mitigation
Patched in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. The fix will be included in TensorFlow 2.10.0, and the commit will be cherry-picked to TensorFlow 2.9.1, 2.8.1 and 2.7.2. There are no known workarounds.
Affected packages in the Exposure Registry
Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.
- tensorflowPyPINo LLM dependency detected · 26 tracked dependents
- tensorflow-gpuPyPINo LLM dependency detected · 2 tracked dependents
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