ghsa-393f-2jr3-cp69
Vulnerability from github
Published
2021-05-21 14:22
Modified
2024-10-30 23:22
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
Summary
CHECK-fail in DrawBoundingBoxes
Details

Impact

An attacker can trigger a denial of service via a CHECK failure by passing an empty image to tf.raw_ops.DrawBoundingBoxes:

```python import tensorflow as tf

images = tf.fill([53, 0, 48, 1], 0.) boxes = tf.fill([53, 31, 4], 0.) boxes = tf.Variable(boxes) boxes[0, 0, 0].assign(3.90621) tf.raw_ops.DrawBoundingBoxes(images=images, boxes=boxes) ```

This is because the implementation uses CHECK_* assertions instead of OP_REQUIRES to validate user controlled inputs. Whereas OP_REQUIRES allows returning an error condition back to the user, the CHECK_* macros result in a crash if the condition is false, similar to assert.

cc const int64 max_box_row_clamp = std::min<int64>(max_box_row, height - 1); ... CHECK_GE(max_box_row_clamp, 0);

In this case, height is 0 from the images input. This results in max_box_row_clamp being negative and the assertion being falsified, followed by aborting program execution.

Patches

We have patched the issue in GitHub commit b432a38fe0e1b4b904a6c222cbce794c39703e87.

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 Yakun Zhang and Ying Wang of Baidu X-Team.

Show details on source website

To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
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  ],
  "aliases": [
    "CVE-2021-29533"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-754"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T22:50:31Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`:\n\n```python\nimport tensorflow as tf\n\nimages = tf.fill([53, 0, 48, 1], 0.)\nboxes = tf.fill([53, 31, 4], 0.)\nboxes = tf.Variable(boxes)\nboxes[0, 0, 0].assign(3.90621)\ntf.raw_ops.DrawBoundingBoxes(images=images, boxes=boxes)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`.\n\n```cc\nconst int64 max_box_row_clamp = std::min\u003cint64\u003e(max_box_row, height - 1);\n... \nCHECK_GE(max_box_row_clamp, 0);\n``` \n    \nIn this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution.\n    \n### Patches\nWe have patched the issue in GitHub commit [b432a38fe0e1b4b904a6c222cbce794c39703e87](https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87).\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 Yakun Zhang and Ying Wang of Baidu X-Team.",
  "id": "GHSA-393f-2jr3-cp69",
  "modified": "2024-10-30T23:22:16Z",
  "published": "2021-05-21T14:22:21Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29533"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-461.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-659.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-170.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "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": "CHECK-fail in DrawBoundingBoxes"
}


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