CVE-2021-37636 (GCVE-0-2021-37636)

Vulnerability from cvelistv5 – Published: 2021-08-12 17:30 – Updated: 2024-08-04 01:23
VLAI
Title
Floating point exception in `SparseDenseCwiseDiv` in TensorFlow
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error. The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. We have patched the issue in GitHub commit d9204be9f49520cdaaeb2541d1dc5187b23f31d9. 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
5.5 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CWE
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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              "type": "Primary"
            }
          ]
        },
        "published": "2021-08-12T18:15:10.377",
        "references": [
          {
            "source": "security-advisories@github.com",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9"
          },
          {
            "source": "security-advisories@github.com",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hp4c-x6r7-6555"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hp4c-x6r7-6555"
          }
        ],
        "sourceIdentifier": "security-advisories@github.com",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-369"
              }
            ],
            "source": "security-advisories@github.com",
            "type": "Primary"
          }
        ]
      }
    },
    "redhat_vex": {
      "current_release_date": "2026-03-27T13:45:08+00:00",
      "cve": "CVE-2021-37636",
      "id": "CVE-2021-37636",
      "initial_release_date": "2021-01-01T00:00:00+00:00",
      "product_status:known_not_affected": "1",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "Floating point exception in `SparseDenseCwiseDiv` in TensorFlow",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-37636.json",
      "version": "3"
    },
    "suse_vex": {
      "aggregate_severity": "important",
      "current_release_date": "2025-03-15T08:47:42Z",
      "cve": "CVE-2021-37636",
      "id": "CVE-2021-37636",
      "initial_release_date": "2023-02-15T03:39:30Z",
      "product_status:recommended": "56",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2021-37636",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2021-37636.json",
      "version": "6"
    }
  }
}



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Tags
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.



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.