ghsa-rf3h-xgv5-2q39
Vulnerability from github
Impact
The implementation of the DepthwiseConv
TFLite operator is vulnerable to a division by zero error:
cc
int num_input_channels = SizeOfDimension(input, 3);
TF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0);
An attacker can craft a model such that input
's fourth dimension would be 0.
Patches
We have patched the issue in GitHub commit cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0.
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 members of the Aivul Team from Qihoo 360.
{ "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-2021-29602" ], "database_specific": { "cwe_ids": [ "CWE-369" ], "github_reviewed": true, "github_reviewed_at": "2021-05-17T22:29:55Z", "nvd_published_at": "2021-05-14T20:15:00Z", "severity": "LOW" }, "details": "### Impact\nThe implementation of the `DepthwiseConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288):\n\n```cc\nint num_input_channels = SizeOfDimension(input, 3);\nTF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0);\n```\n\nAn attacker can craft a model such that `input`\u0027s fourth dimension would be 0.\n\n### Patches\nWe have patched the issue in GitHub commit [cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0](https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0).\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 members of the Aivul Team from Qihoo 360.", "id": "GHSA-rf3h-xgv5-2q39", "modified": "2024-11-13T16:08:49Z", "published": "2021-05-21T14:28:12Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rf3h-xgv5-2q39" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29602" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-530.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-728.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-239.yaml" }, { "type": "PACKAGE", "url": "https://github.com/tensorflow/tensorflow" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288" } ], "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 zero in TFLite\u0027s implementation of `DepthwiseConv`" }
Sightings
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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.