Vulnerability-Lookup

PYSEC-2021-461

Vulnerability from pysec - Published: 2021-05-14 20:15 - Updated: 2021-12-09 06:34

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a CHECK failure by passing an empty image to tf.raw_ops.DrawBoundingBoxes. This 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. 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. 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.

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"
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            {
              "fixed": "b432a38fe0e1b4b904a6c222cbce794c39703e87"
            }
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          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
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              "fixed": "2.2.0rc0"
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            {
              "fixed": "2.3.0rc0"
            },
            {
              "introduced": "2.3.0"
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            {
              "fixed": "2.3.4"
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              "introduced": "2.4.0"
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            {
              "fixed": "2.4.3"
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          "type": "ECOSYSTEM"
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      "versions": [
        "1.15.0",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.4.0",
        "2.4.1",
        "2.4.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29533",
    "GHSA-393f-2jr3-cp69"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This 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`. 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. 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.",
  "id": "PYSEC-2021-461",
  "modified": "2021-12-09T06:34:48.500169Z",
  "published": "2021-05-14T20:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-393f-2jr3-cp69"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/b432a38fe0e1b4b904a6c222cbce794c39703e87"
    }
  ]
}

CVE-2021-29533 (GCVE-0-2021-29533)

Vulnerability from cvelistv5 – Published: 2021-05-14 19:12 – Updated: 2024-08-03 22:11

Title

CHECK-fail in DrawBoundingBoxes

Summary

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This 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`. 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. 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.

Severity ?

2.5 (Low)


                        
                          CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L

CWE

CWE-754 - Improper Check for Unusual or Exceptional Conditions

Assigner

GitHub_M

References

URL

Tags

	https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/b…	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Affected: < 2.1.4 Affected: >= 2.2.0, < 2.2.3 Affected: >= 2.3.0, < 2.3.3 Affected: >= 2.4.0, < 2.4.2

Show details on NVD website

JSON

To clipboard

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GHSA-393F-2JR3-CP69

Vulnerability from github – Published: 2021-05-21 14:22 – Updated: 2024-10-30 23:22

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:

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.

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.

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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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            {
              "introduced": "2.2.0"
            },
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              "fixed": "2.2.3"
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          "type": "ECOSYSTEM"
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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              "introduced": "2.3.0"
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        "name": "tensorflow-gpu"
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        {
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            },
            {
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            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
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              "introduced": "2.3.0"
            },
            {
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            }
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          "type": "ECOSYSTEM"
        }
      ]
    },
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
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            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "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"
}

Sightings

Author	Source	Type	Date

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.

Detection rules are retrieved from Rulezet.

Action not permitted

PYSEC-2021-461

CVE-2021-29533 (GCVE-0-2021-29533)

GHSA-393F-2JR3-CP69

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature