MediumVulnerability
CVE-2022-36017: TensorFlow segfault in Requantize with nonzero rank tensors
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2022-36017
- 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 `Requantize` op crashes with a segfault when `input_min`, `input_max`, `requested_output_min` or `requested_output_max` is given as a tensor of nonzero rank, enabling a denial of service attack. The issue is tracked as CVE-2022-36017 and was patched in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.
Mitigation
Fixed in TensorFlow 2.10.0. The commit will also be cherry-picked to TensorFlow 2.9.1, 2.8.1 and 2.7.2, which are affected and still in supported range. 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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