GHSA-75f6-78jr-4656
Vulnerability from github
Impact
An attacker can trigger a null pointer dereference in the implementation of tf.raw_ops.EditDistance
:
```python import tensorflow as tf
hypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64) hypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32) hypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64) truth_indices = tf.constant([], shape=[0, 3], dtype=tf.int64) truth_values = tf.constant([], shape=[0], dtype=tf.float32) truth_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)
tf.raw_ops.EditDistance( hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values, hypothesis_shape=hypothesis_shape, truth_indices=truth_indices, truth_values=truth_values, truth_shape=truth_shape, normalize=True) ```
This is because the implementation has incomplete validation of the input parameters.
In the above scenario, an attacker causes an allocation of an empty tensor for the output:
cc
OP_REQUIRES_OK(ctx, ctx->allocate_output("output", output_shape, &output));
auto output_t = output->flat<float>();
output_t.setZero();
Because output_shape
has 0 elements, the result of output->flat<T>()
has an empty buffer, so calling setZero
would result in a null dereference.
Patches
We have patched the issue in GitHub commit f4c364a5d6880557f6f5b6eb5cee2c407f0186b3.
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.
{ "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" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.4.0" }, { "fixed": "2.4.2" } ], "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-2021-29564" ], "database_specific": { "cwe_ids": [ "CWE-476" ], "github_reviewed": true, "github_reviewed_at": "2021-05-18T19:43:25Z", "nvd_published_at": "2021-05-14T20:15:00Z", "severity": "LOW" }, "details": "### Impact\nAn attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`: \n \n```python\nimport tensorflow as tf\n\nhypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64)\nhypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32)\nhypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)\ntruth_indices = tf.constant([], shape=[0, 3], dtype=tf.int64)\ntruth_values = tf.constant([], shape=[0], dtype=tf.float32)\ntruth_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)\n\ntf.raw_ops.EditDistance(\n hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values,\n hypothesis_shape=hypothesis_shape, truth_indices=truth_indices,\n truth_values=truth_values, truth_shape=truth_shape, normalize=True)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters.\n\nIn the above scenario, an attacker causes an allocation of an empty tensor for the output:\n\n```cc\nOP_REQUIRES_OK(ctx, ctx-\u003eallocate_output(\"output\", output_shape, \u0026output));\nauto output_t = output-\u003eflat\u003cfloat\u003e();\noutput_t.setZero();\n```\n\nBecause `output_shape` has 0 elements, the result of `output-\u003eflat\u003cT\u003e()` has an empty buffer, so calling `setZero` would result in a null dereference.\n\n### Patches\nWe have patched the issue in GitHub commit [f4c364a5d6880557f6f5b6eb5cee2c407f0186b3](https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3).\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-75f6-78jr-4656", "modified": "2024-11-01T16:54:25Z", "published": "2021-05-21T14:25:08Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-75f6-78jr-4656" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29564" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-492.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-690.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-201.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": "Null pointer dereference in `EditDistance`" }
Sightings
Author | Source | Type | Date |
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Nomenclature
- Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
- Confirmed: The vulnerability is confirmed from an analyst perspective.
- Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
- Patched: This vulnerability was successfully patched by the user reporting the sighting.
- Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
- Not confirmed: The user expresses doubt about the veracity of the vulnerability.
- Not patched: This vulnerability was not successfully patched by the user reporting the sighting.