ghsa-2r2f-g8mw-9gvr
Vulnerability from github
Impact
The implementation of tf.raw_ops.EditDistance has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:
```python import tensorflow as tf
hypothesis_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) hypothesis_values = tf.constant(0, shape=[3], dtype=tf.int64) hypothesis_shape = tf.constant(0, shape=[3], dtype=tf.int64)
truth_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) truth_values = tf.constant(2, shape=[3], dtype=tf.int64) truth_shape = tf.constant(2, 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) ```
In multiple places throughout the code, we are computing an index for a write operation:
cc
if (g_truth == g_hypothesis) {
auto loc = std::inner_product(g_truth.begin(), g_truth.end(),
output_strides.begin(), int64_t{0});
OP_REQUIRES(
ctx, loc < output_elements,
errors::Internal("Got an inner product ", loc,
" which would require in writing to outside of "
"the buffer for the output tensor (max elements ",
output_elements, ")"));
output_t(loc) =
gtl::LevenshteinDistance<T>(truth_seq, hypothesis_seq, cmp);
// ...
}
However, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for loc.
Patches
We have patched the issue in GitHub commit 30721cf564cb029d34535446d6a5a6357bebc8e7.
The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
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}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-cpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.6.4"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.7.0"
},
{
"fixed": "2.7.2"
}
],
"type": "ECOSYSTEM"
}
]
},
{
"package": {
"ecosystem": "PyPI",
"name": "tensorflow-gpu"
},
"ranges": [
{
"events": [
{
"introduced": "2.8.0"
},
{
"fixed": "2.8.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2022-29208"
],
"database_specific": {
"cwe_ids": [
"CWE-787"
],
"github_reviewed": true,
"github_reviewed_at": "2022-05-24T22:14:22Z",
"nvd_published_at": "2022-05-20T23:15:00Z",
"severity": "HIGH"
},
"details": "### Impact\nThe implementation of [`tf.raw_ops.EditDistance`]() has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service:\n\n```python\nimport tensorflow as tf\n\nhypothesis_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) \nhypothesis_values = tf.constant(0, shape=[3], dtype=tf.int64)\nhypothesis_shape = tf.constant(0, shape=[3], dtype=tf.int64)\n\ntruth_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64)\ntruth_values = tf.constant(2, shape=[3], dtype=tf.int64)\ntruth_shape = tf.constant(2, shape=[3], dtype=tf.int64) \n\ntf.raw_ops.EditDistance(\n hypothesis_indices=hypothesis_indices,\n hypothesis_values=hypothesis_values,\n hypothesis_shape=hypothesis_shape,\n truth_indices=truth_indices,\n truth_values=truth_values,\n truth_shape=truth_shape)\n```\n\nIn multiple places throughout the code, we are computing an index for a write operation:\n\n```cc\nif (g_truth == g_hypothesis) {\n auto loc = std::inner_product(g_truth.begin(), g_truth.end(),\n output_strides.begin(), int64_t{0});\n OP_REQUIRES(\n ctx, loc \u003c output_elements,\n errors::Internal(\"Got an inner product \", loc,\n \" which would require in writing to outside of \"\n \"the buffer for the output tensor (max elements \",\n output_elements, \")\"));\n output_t(loc) =\n gtl::LevenshteinDistance\u003cT\u003e(truth_seq, hypothesis_seq, cmp);\n // ...\n}\n```\n\nHowever, the existing validation only checks against the upper bound of the array. Hence, it is possible to write before the array by massaging the input to generate negative values for `loc`.\n\n### Patches\nWe have patched the issue in GitHub commit [30721cf564cb029d34535446d6a5a6357bebc8e7](https://github.com/tensorflow/tensorflow/commit/30721cf564cb029d34535446d6a5a6357bebc8e7).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.",
"id": "GHSA-2r2f-g8mw-9gvr",
"modified": "2022-06-06T18:15:08Z",
"published": "2022-05-24T22:14:22Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-2r2f-g8mw-9gvr"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2022-29208"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/30721cf564cb029d34535446d6a5a6357bebc8e7"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "Segfault and OOB write due to incomplete validation in `EditDistance` in TensorFlow"
}
Sightings
| Author | Source | Type | Date |
|---|
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.