LowVulnerability
CVE-2021-29523: TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via…
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2021-29523
- 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 contains a denial-of-service flaw in tf.raw_ops.AddManySparseToTensorsMap. Values in sparse_shape are used as output shape dimensions, and the legacy TensorShape constructor hits a CHECK failure when InitDims returns a non-OK status, which an attacker can trigger.
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 code should use BuildTensorShapeBase or AddDimWithStatus instead of the legacy constructor.
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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