MediumVulnerability
CVE-2020-15197: Tensorflow SparseCountSparseOutput crash from unvalidated sparse tensor input
- Source
- NVD(opens in a new tab)
- Identifier
- CVE-2020-15197
- Published
- Record updated
- Affected
- tensorflow = 2.3.0
- tensorflow-cpu = 2.3.0
- tensorflow-gpu = 2.3.0
- Fixed in
- 2.3.1
- tensorflow 2.3.1 released September 24, 2020, 1 day before disclosure
- tensorflow-cpu 2.3.1 released September 24, 2020, 1 day before disclosure
- tensorflow-gpu 2.3.1 released September 24, 2020, 1 day before disclosure
- Known exploitation
- Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
- EPSS
- 0.7%
Summary
In TensorFlow before 2.3.1, the `SparseCountSparseOutput` implementation does not check that its input forms a valid sparse tensor, and in particular does not verify that the `indices` tensor has rank 2. A malicious user can pass a tensor of a different rank, triggering a `CHECK` assertion failure and a crash. Where users can control the components of the input sparse tensor, this enables denial of service in serving installations.
Mitigation
The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and released in TensorFlow version 2.3.1.
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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