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CVE-2021-37689 (GCVE-0-2021-37689)

Vulnerability from cvelistv5 – Published: 2021-08-12 22:00 – Updated: 2024-08-04 01:23
VLAI
Title
Null pointer dereference in TensorFlow Lite MLIR optimizations
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can craft a TFLite model that would trigger a null pointer dereference, which would result in a crash and denial of service. This is caused by the MLIR optimization of `L2NormalizeReduceAxis` operator. The [implementation](https://github.com/tensorflow/tensorflow/blob/149562d49faa709ea80df1d99fc41d005b81082a/tensorflow/compiler/mlir/lite/transforms/optimize.cc#L67-L70) unconditionally dereferences a pointer to an iterator to a vector without checking that the vector has elements. We have patched the issue in GitHub commit d6b57f461b39fd1aa8c1b870f1b974aac3554955. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Severity
7.8 (High)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CWE
  • CWE-476 - NULL Pointer Dereference
Assigner
References
Impacted products
Vendor Product Version CPE status
tensorflow tensorflow Affected: >= 2.5.0, < 2.5.1
Affected: >= 2.4.0, < 2.4.3
Affected: < 2.3.4
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      "status": "final",
      "title": "Null pointer dereference in TensorFlow Lite MLIR optimizations",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-37689.json",
      "version": "3"
    },
    "suse_vex": {
      "aggregate_severity": "important",
      "current_release_date": "2025-03-15T08:46:36Z",
      "cve": "CVE-2021-37689",
      "id": "CVE-2021-37689",
      "initial_release_date": "2023-02-15T03:39:15Z",
      "product_status:recommended": "56",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2021-37689",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2021-37689.json",
      "version": "6"
    }
  }
}



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Taxonomy of the tags.





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.


Related by attack behaviour

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.