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AI Sec Watch
MediumVulnerability

CVE-2020-15213: TensorFlow Lite denial of service through segment sum models

Source
NVD(opens in a new tab)
Identifier
CVE-2020-15213
Published
Record updated
View JSON
Affected
  • tensorflow = 2.2.0, fixed in 2.2.1, released September 24, 2020, 1 day before disclosure
  • tensorflow = 2.3.0, fixed in 2.3.1, released September 24, 2020, 1 day before disclosure
  • tensorflow-cpu = 2.2.0, fixed in 2.2.1, released September 24, 2020, 1 day before disclosure
  • and 3 more
Known exploitation
Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS
0.8%

Summary

TensorFlow Lite versions before 2.2.1 and 2.3.1 are affected by CVE-2020-15213. Models that use segment sum can trigger an out of memory allocation, causing a denial of service. The output tensor's dimensionality is taken from the last element of the segment ids tensor, so an attacker can supply a very large value to force a large allocation.

Mitigation

Fixed in commit 204945b19e44b57906c9344c0d00120eeeae178a, released in TensorFlow 2.2.1 and 2.3.1. A potential workaround is a custom `Verifier` that limits the maximum value in the segment ids tensor, which only covers segment ids stored statically in the model. If segment ids are generated as outputs of a tensor during inference, no workaround is possible and users are advised to upgrade to patched code.

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.

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