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CVE-2020-15198 (GCVE-0-2020-15198)

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 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 the same shape as the `values` one. The values in these tensors are always accessed in parallel. Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.
Severity
5.4 (Medium)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:N
CWE
  • CWE-122 - {"CWE-122":"Heap-based Buffer Overflow"}
  • CWE-119 - {"CWE-119":"Improper Restriction of Operations within the Bounds of a Memory Buffer"}
Assigner
References
Impacted products
Vendor Product Version CPE status
tensorflow tensorflow Affected: >= 2.3.0, < 2.3.1
guessed Create a notification for this product.
Show details on NVD website
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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • 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.


Detection rules are retrieved from Rulezet.


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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.