ghsa-f2w8-jw48-fr7j
Vulnerability from github
Impact
If FractionMaxPoolGrad
is given outsize inputs row_pooling_sequence
and col_pooling_sequence
, TensorFlow will crash.
python
import tensorflow as tf
tf.raw_ops.FractionMaxPoolGrad(
orig_input = [[[[1, 1, 1, 1, 1]]]],
orig_output = [[[[1, 1, 1]]]],
out_backprop = [[[[3], [3], [6]]]],
row_pooling_sequence = [-0x4000000, 1, 1],
col_pooling_sequence = [-0x4000000, 1, 1],
overlapping = False
)
Patches
We have patched the issue in GitHub commit d71090c3e5ca325bdf4b02eb236cfb3ee823e927.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Vul AI.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.8.4" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.9.0" }, { "fixed": "2.9.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.10.0" }, { "fixed": "2.10.1" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.8.4" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.8.4" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.9.0" }, { "fixed": "2.9.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.9.0" }, { "fixed": "2.9.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.10.0" }, { "fixed": "2.10.1" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.10.0" }, { "fixed": "2.10.1" } ], "type": "ECOSYSTEM" } ] } ], "aliases": [ "CVE-2022-41897" ], "database_specific": { "cwe_ids": [ "CWE-125" ], "github_reviewed": true, "github_reviewed_at": "2022-11-21T21:54:04Z", "nvd_published_at": "2022-11-18T22:15:00Z", "severity": "MODERATE" }, "details": "### Impact\nIf [`FractionMaxPoolGrad`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc) is given outsize inputs `row_pooling_sequence` and `col_pooling_sequence`, TensorFlow will crash.\n\n```python\nimport tensorflow as tf\ntf.raw_ops.FractionMaxPoolGrad(\n\torig_input = [[[[1, 1, 1, 1, 1]]]],\n orig_output = [[[[1, 1, 1]]]],\n out_backprop = [[[[3], [3], [6]]]],\n row_pooling_sequence = [-0x4000000, 1, 1], \n col_pooling_sequence = [-0x4000000, 1, 1], \n overlapping = False\n )\n```\n\n### Patches\nWe have patched the issue in GitHub commit [d71090c3e5ca325bdf4b02eb236cfb3ee823e927](https://github.com/tensorflow/tensorflow/commit/d71090c3e5ca325bdf4b02eb236cfb3ee823e927).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.\n\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\n### Attribution\nThis vulnerability has been reported by Vul AI.\n", "id": "GHSA-f2w8-jw48-fr7j", "modified": "2022-11-21T21:54:04Z", "published": "2022-11-21T21:54:04Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2w8-jw48-fr7j" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41897" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/d71090c3e5ca325bdf4b02eb236cfb3ee823e927" }, { "type": "PACKAGE", "url": "https://github.com/tensorflow/tensorflow" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc" } ], "schema_version": "1.4.0", "severity": [ { "score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H", "type": "CVSS_V3" } ], "summary": "`FractionalMaxPoolGrad` Heap out of bounds read" }
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.