GHSA-RWW7-2GPW-FV6J

Vulnerability from github – Published: 2022-02-09 23:28 – Updated: 2024-11-13 22:46
VLAI?
Summary
Crash when type cannot be specialized in Tensorflow
Details

Impact

Under certain scenarios, TensorFlow can fail to specialize a type during shape inference:

void InferenceContext::PreInputInit(
    const OpDef& op_def, const std::vector<const Tensor*>& input_tensors,
    const std::vector<ShapeHandle>& input_tensors_as_shapes) {
  const auto ret = full_type::SpecializeType(attrs_, op_def);
  DCHECK(ret.status().ok()) << "while instantiating types: " << ret.status();
  ret_types_ = ret.ValueOrDie();
  // ... 
}

However, DCHECK is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the ValueOrDie line. This results in an assertion failure as ret contains an error Status, not a value. In the second case we also get a crash due to the assertion failure.

Patches

We have patched the issue in GitHub commit cb164786dc891ea11d3a900e90367c339305dc7b.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.

For more information

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

Severity ?
6.5 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
7.1 (High)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Show details on source website
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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-23572"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617",
      "CWE-754"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-04T18:58:49Z",
    "nvd_published_at": "2022-02-04T23:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nUnder certain scenarios, TensorFlow can fail to specialize a type during [shape inference](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174):\n\n```cc\nvoid InferenceContext::PreInputInit(\n    const OpDef\u0026 op_def, const std::vector\u003cconst Tensor*\u003e\u0026 input_tensors,\n    const std::vector\u003cShapeHandle\u003e\u0026 input_tensors_as_shapes) {\n  const auto ret = full_type::SpecializeType(attrs_, op_def);\n  DCHECK(ret.status().ok()) \u003c\u003c \"while instantiating types: \" \u003c\u003c ret.status();\n  ret_types_ = ret.ValueOrDie();\n  // ... \n}\n```\n\nHowever, `DCHECK` is a no-op in production builds and an assertion failure in debug builds. In the first case execution proceeds to the `ValueOrDie` line. This results in an assertion failure as `ret` contains an error `Status`, not a value. In the second case we also get a crash due to the assertion failure.\n### Patches\nWe have patched the issue in GitHub commit [cb164786dc891ea11d3a900e90367c339305dc7b](https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, and TensorFlow 2.6.3, as these are also affected and still in supported range.\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-rww7-2gpw-fv6j",
  "modified": "2024-11-13T22:46:57Z",
  "published": "2022-02-09T23:28:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rww7-2gpw-fv6j"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23572"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/cb164786dc891ea11d3a900e90367c339305dc7b"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-81.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-136.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/shape_inference.cc#L168-L174"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Crash when type cannot be specialized in Tensorflow"
}


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