CVE-2020-15197 (GCVE-0-2020-15197)

Vulnerability from cvelistv5 – Published: 2020-09-25 18:40 – Updated: 2024-08-04 13:08
VLAI?
Title
Denial of Service in Tensorflow
Summary
In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Severity ?
6.3 (Medium)
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H
CWE
  • CWE-617 - {"CWE-617":"Reachable Assertion"}
  • CWE-20 - {"CWE-20":"Improper Input Validation"}
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: = 2.3.0
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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
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  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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