GHSA-p45v-v4pw-77jr
Vulnerability from github
Published
2021-05-21 14:23
Modified
2024-10-31 20:46
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
Division by 0 in `QuantizedBatchNormWithGlobalNormalization`
Details

Impact

An attacker can cause a runtime division by zero error and denial of service in tf.raw_ops.QuantizedBatchNormWithGlobalNormalization:

```python import tensorflow as tf

t = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8) t_min = tf.constant(-10.0, dtype=tf.float32) t_max = tf.constant(-10.0, dtype=tf.float32) m = tf.constant([], shape=[0], dtype=tf.quint8) m_min = tf.constant(-10.0, dtype=tf.float32) m_max = tf.constant(-10.0, dtype=tf.float32) v = tf.constant([], shape=[0], dtype=tf.quint8) v_min = tf.constant(-10.0, dtype=tf.float32) v_max = tf.constant(-10.0, dtype=tf.float32) beta = tf.constant([], shape=[0], dtype=tf.quint8) beta_min = tf.constant(-10.0, dtype=tf.float32) beta_max = tf.constant(-10.0, dtype=tf.float32) gamma = tf.constant([], shape=[0], dtype=tf.quint8) gamma_min = tf.constant(-10.0, dtype=tf.float32) gamma_max = tf.constant(-10.0, dtype=tf.float32)

tf.raw_ops.QuantizedBatchNormWithGlobalNormalization( t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max, v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min, beta_max=beta_max, gamma=gamma, gamma_min=gamma_min, gamma_max=gamma_max, out_type=tf.qint32, variance_epsilon=0.1, scale_after_normalization=True) ```

This is because the implementation does not validate all constraints specified in the op's contract.

Patches

We have patched the issue in GitHub commit d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b.

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"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
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          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
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          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29548"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-369"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T21:30:45Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can cause a runtime division by zero error and denial of service in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`:\n\n```python\nimport tensorflow as tf\n\nt = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.quint8)\nt_min = tf.constant(-10.0, dtype=tf.float32)\nt_max = tf.constant(-10.0, dtype=tf.float32)\nm = tf.constant([], shape=[0], dtype=tf.quint8)\nm_min = tf.constant(-10.0, dtype=tf.float32)\nm_max = tf.constant(-10.0, dtype=tf.float32)\nv = tf.constant([], shape=[0], dtype=tf.quint8)\nv_min = tf.constant(-10.0, dtype=tf.float32)\nv_max = tf.constant(-10.0, dtype=tf.float32)\nbeta = tf.constant([], shape=[0], dtype=tf.quint8)\nbeta_min = tf.constant(-10.0, dtype=tf.float32)\nbeta_max = tf.constant(-10.0, dtype=tf.float32)\ngamma = tf.constant([], shape=[0], dtype=tf.quint8)\ngamma_min = tf.constant(-10.0, dtype=tf.float32)\ngamma_max = tf.constant(-10.0, dtype=tf.float32)\n\ntf.raw_ops.QuantizedBatchNormWithGlobalNormalization(\n  t=t, t_min=t_min, t_max=t_max, m=m, m_min=m_min, m_max=m_max,\n  v=v, v_min=v_min, v_max=v_max, beta=beta, beta_min=beta_min,\n  beta_max=beta_max, gamma=gamma, gamma_min=gamma_min,\n  gamma_max=gamma_max, out_type=tf.qint32,\n  variance_epsilon=0.1, scale_after_normalization=True)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc) does not validate all constraints specified in the [op\u0027s contract](https://www.tensorflow.org/api_docs/python/tf/raw_ops/QuantizedBatchNormWithGlobalNormalization).\n\n### Patches \nWe have patched the issue in GitHub commit [d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b](https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b).\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-p45v-v4pw-77jr",
  "modified": "2024-10-31T20:46:23Z",
  "published": "2021-05-21T14:23:34Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p45v-v4pw-77jr"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29548"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/d6ed5bcfe1dcab9e85a4d39931bd18d99018e75b"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-476.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-674.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-185.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": "Division by 0 in `QuantizedBatchNormWithGlobalNormalization`"
}


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