GHSA-VF94-36G5-69V8

Vulnerability from github – Published: 2021-05-21 14:27 – Updated: 2024-11-13 16:02
VLAI?
Summary
Division by zero in TFLite's implementation of `DepthToSpace`
Details

Impact

The implementation of the DepthToSpace TFLite operator is vulnerable to a division by zero error:

const int block_size = params->block_size;
...
const int input_channels = input->dims->data[3];
... 
int output_channels = input_channels / block_size / block_size;

An attacker can craft a model such that params->block_size is 0.

Patches

We have patched the issue in GitHub commit 106d8f4fb89335a2c52d7c895b7a7485465ca8d9.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Severity ?
2.5 (Low)
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
2.0 (Low)
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
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        "name": "tensorflow"
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  "aliases": [
    "CVE-2021-29595"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-17T23:06:31Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nThe implementation of the `DepthToSpace` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depth_to_space.cc#L63-L69):\n\n```cc\nconst int block_size = params-\u003eblock_size;\n...\nconst int input_channels = input-\u003edims-\u003edata[3];\n... \nint output_channels = input_channels / block_size / block_size;\n``` \n\nAn attacker can craft a model such that `params-\u003eblock_size` is 0.\n\n### Patches\nWe have patched the issue in GitHub commit [106d8f4fb89335a2c52d7c895b7a7485465ca8d9](https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9).\n    \nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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.\n\n### Attribution \nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
  "id": "GHSA-vf94-36g5-69v8",
  "modified": "2024-11-13T16:02:57Z",
  "published": "2021-05-21T14:27:49Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-vf94-36g5-69v8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29595"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-523.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-721.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-232.yaml"
    }
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  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Division by zero in TFLite\u0027s implementation of `DepthToSpace`"
}


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  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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