CVE-2020-15196 (GCVE-0-2020-15196)

Vulnerability from cvelistv5 – Published: 2020-09-25 18:40 – Updated: 2024-08-04 13:08
VLAI?
Title
Heap buffer overflow in Tensorflow
Summary
In Tensorflow version 2.3.0, the `SparseCountSparseOutput` and `RaggedCountSparseOutput` implementations don't validate that the `weights` tensor has the same shape as the data. The check exists for `DenseCountSparseOutput`, where both tensors are fully specified. In the sparse and ragged count weights are still accessed in parallel with the data. But, since there is no validation, a user passing fewer weights than the values for the tensors can generate a read from outside the bounds of the heap buffer allocated for the weights. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Severity ?
8.5 (High)
CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:H/I:H/A:H
CWE
  • CWE-119 - {"CWE-119":"Improper Restriction of Operations within the Bounds of a Memory Buffer"}
  • CWE-122 - {"CWE-122":"Heap-based Buffer Overflow"}
Assigner
References
Impacted products
Vendor Product Version
tensorflow tensorflow Affected: = 2.3.0
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Sightings

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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.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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