ghsa-gf2j-f278-xh4v
Vulnerability from github
7.1 (High) - CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Impact
An attacker can craft a TFLite model that would trigger a division by zero in BiasAndClamp
implementation:
cc
inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
const float* bias_data, int array_size,
float* array_data) {
// ...
TFLITE_DCHECK_EQ((array_size % bias_size), 0);
// ...
}
There is no check that the bias_size
is non zero.
Patches
We have patched the issue in GitHub commit 8c6f391a2282684a25cbfec7687bd5d35261a209.
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Wang Xuan of Qihoo 360 AIVul Team.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.5.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.6.0" }, { "fixed": "2.6.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.7.0" }, { "fixed": "2.7.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.7.0" ] } ], "aliases": [ "CVE-2022-23557" ], "database_specific": { "cwe_ids": [ "CWE-369" ], "github_reviewed": true, "github_reviewed_at": "2022-02-03T20:21:15Z", "nvd_published_at": "2022-02-04T23:15:00Z", "severity": "HIGH" }, "details": "### Impact \nAn attacker can craft a TFLite model that would trigger a division by zero in [`BiasAndClamp` implementation](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75):\n\n```cc\ninline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,\n const float* bias_data, int array_size,\n float* array_data) {\n // ...\n TFLITE_DCHECK_EQ((array_size % bias_size), 0);\n // ...\n} \n```\n \nThere is no check that the `bias_size` is non zero.\n \n### Patches\nWe have patched the issue in GitHub commit [8c6f391a2282684a25cbfec7687bd5d35261a209](https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.\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 Wang Xuan of Qihoo 360 AIVul Team.", "id": "GHSA-gf2j-f278-xh4v", "modified": "2024-11-13T22:35:32Z", "published": "2022-02-09T23:47:57Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-gf2j-f278-xh4v" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23557" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/8c6f391a2282684a25cbfec7687bd5d35261a209" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-66.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-121.yaml" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/lite/kernels/internal/common.h#L75" } ], "schema_version": "1.4.0", "severity": [ { "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H", "type": "CVSS_V3" }, { "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N", "type": "CVSS_V4" } ], "summary": "Division by zero in TFLite" }
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.