LowVulnerability
CVE-2021-29569: TensorFlow out-of-bounds read in tf.raw_ops.MaxPoolGradWithArgmax
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2021-29569
- Published
- Record updated
- Affected
- tensorflow < 2.1.4, fixed in 2.1.4, released June 15, 2021, 31 days after disclosure
- tensorflow >= 2.2.0, < 2.2.3, fixed in 2.2.3, released June 15, 2021, 31 days after disclosure
- tensorflow >= 2.3.0, < 2.3.3, fixed in 2.3.3, released June 15, 2021, 31 days after disclosure
- and 9 more
- Known exploitation
- Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
- EPSS
- 0.2%
Summary
TensorFlow's implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can read outside the bounds of heap-allocated data when an attacker supplies specially crafted inputs. The flaw sits in the requantization range kernel, which assumes the `input_min` and `input_max` tensors contain at least one element and reads their first elements without checking, so empty tensors trigger the out-of-bounds access.
Mitigation
The fix will be included in TensorFlow 2.5.0. The commit will also be cherry-picked to TensorFlow 2.4.2, 2.3.3, 2.2.3 and 2.1.4.
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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