pysec - pysec-2022-102

pysec-2022-102

Vulnerability from pysec

Published

2022-02-04 23:15

Modified

2022-05-23 17:21

Details

Tensorflow is an Open Source Machine Learning Framework. The simplifyBroadcast function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then maxRank is 0, so we build an empty SmallVector. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

Impacted products

Name	purl
tensorflow-cpu	pkg:pypi/tensorflow-cpu

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "35f0fabb4c178253a964d7aabdbb15c6a398b69a"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.8.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0",
        "2.7.1",
        "2.8.0rc0",
        "2.8.0rc1",
        "2.7.2",
        "2.7.3"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-23593",
    "GHSA-gwcx-jrx4-92w2"
  ],
  "details": "Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.",
  "id": "PYSEC-2022-102",
  "modified": "2022-05-23T17:21:57.130120Z",
  "published": "2022-02-04T23:15:00Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gwcx-jrx4-92w2"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a"
    }
  ]
}

CVE-2022-23593 (GCVE-0-2022-23593)

Vulnerability from cvelistv5

Published

2022-02-04 22:32

Modified

2025-04-22 18:27

Severity ?

5.9 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

CWE

CWE-754 - Improper Check for Unusual or Exceptional Conditions

Summary

Tensorflow is an Open Source Machine Learning Framework. The `simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes. If all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`. The fix will be included in TensorFlow 2.8.0. This is the only affected version.

References

URL

Tags

	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gwcx-jrx4-92w2	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Version: >= 2.7.0, < 2.8.0

Show details on NVD website

JSON

To clipboard

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ghsa-gwcx-jrx4-92w2

Vulnerability from github

Published

2022-02-09 23:32

Modified

2024-11-13 22:16

Severity ?

5.9 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
8.2 (High) - CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Summary

Segfault in `simplifyBroadcast` in Tensorflow

Details

Impact

The simplifyBroadcast function in the MLIR-TFRT infrastructure in TensorFlow is vulnerable to a segfault (hence, denial of service), if called with scalar shapes.

```cc size_t maxRank = 0; for (auto shape : llvm::enumerate(shapes)) { auto found_shape = analysis.dimensionsForShapeTensor(shape.value()); if (!found_shape) return {}; shapes_found.push_back(*found_shape); maxRank = std::max(maxRank, found_shape->size()); }

SmallVector joined_dimensions(maxRank); ```

If all shapes are scalar, then maxRank is 0, so we build an empty SmallVector.

Patches

We have patched the issue in GitHub commit 35f0fabb4c178253a964d7aabdbb15c6a398b69a.

The fix will be included in TensorFlow 2.8.0. This is the only affected version.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0-rc0"
            },
            {
              "fixed": "2.8.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.8.0-rc0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0-rc0"
            },
            {
              "fixed": "2.8.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.8.0-rc0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0-rc0"
            },
            {
              "fixed": "2.8.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.8.0-rc0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-23593"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-754"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-04T18:15:07Z",
    "nvd_published_at": "2022-02-04T23:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nThe [`simplifyBroadcast` function in the MLIR-TFRT infrastructure in TensorFlow](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205) is vulnerable to a segfault (hence, denial of service), if called with scalar shapes.\n\n```cc \n  size_t maxRank = 0;\n  for (auto shape : llvm::enumerate(shapes)) {\n    auto found_shape = analysis.dimensionsForShapeTensor(shape.value());\n    if (!found_shape) return {};\n    shapes_found.push_back(*found_shape);\n    maxRank = std::max(maxRank, found_shape-\u003esize());\n  }   \n\n  SmallVector\u003cconst ShapeComponentAnalysis::SymbolicDimension*\u003e\n      joined_dimensions(maxRank);\n```\n\nIf all shapes are scalar, then `maxRank` is 0, so we build an empty `SmallVector`.\n\n### Patches\nWe have patched the issue in GitHub commit [35f0fabb4c178253a964d7aabdbb15c6a398b69a](https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a).\n\nThe fix will be included in TensorFlow 2.8.0. This is the only affected version.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.",
  "id": "GHSA-gwcx-jrx4-92w2",
  "modified": "2024-11-13T22:16:35Z",
  "published": "2022-02-09T23:32:08Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gwcx-jrx4-92w2"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23593"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/35f0fabb4c178253a964d7aabdbb15c6a398b69a"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-102.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-157.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/mlir/tfrt/jit/transforms/tf_cpurt_symbolic_shape_optimization.cc#L149-L205"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Segfault in `simplifyBroadcast` in Tensorflow"
}

Sightings

Author	Source	Type	Date

Nomenclature

Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
Confirmed: The vulnerability is confirmed from an analyst perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
Patched: This vulnerability was successfully patched by the user reporting the sighting.
Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
Not confirmed: The user expresses doubt about the veracity of the vulnerability.
Not patched: This vulnerability was not successfully patched by the user reporting the sighting.

Action not permitted

pysec-2022-102

Vulnerability from pysec

CVE-2022-23593 (GCVE-0-2022-23593)

Vulnerability from cvelistv5

ghsa-gwcx-jrx4-92w2

Vulnerability from github

Impact

Patches

For more information

Tags

Sightings

Nomenclature