GHSA-9w2p-5mgw-p94c
Vulnerability from github
5.7 (Medium) - CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
Impact
The implementation of tf.raw_ops.QuantizeAndDequantizeV4Grad
is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value.
```python import tensorflow as tf
tf.raw_ops.QuantizeAndDequantizeV4Grad( gradients=[1.0,2.0], input=[1.0,1.0], input_min=[0.0], input_max=[10.0], axis=-100) ```
The implementation uses the axis
value as the size argument to absl::InlinedVector
constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer.
Patches
We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1.
The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, 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 members of the Aivul Team from Qihoo 360.
{ "affected": [ { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.4.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow" }, "ranges": [ { "events": [ { "introduced": "2.5.0" }, { "fixed": "2.5.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.5.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.4.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-cpu" }, "ranges": [ { "events": [ { "introduced": "2.5.0" }, { "fixed": "2.5.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.5.0" ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "0" }, { "fixed": "2.4.3" } ], "type": "ECOSYSTEM" } ] }, { "package": { "ecosystem": "PyPI", "name": "tensorflow-gpu" }, "ranges": [ { "events": [ { "introduced": "2.5.0" }, { "fixed": "2.5.1" } ], "type": "ECOSYSTEM" } ], "versions": [ "2.5.0" ] } ], "aliases": [ "CVE-2021-37645" ], "database_specific": { "cwe_ids": [ "CWE-681" ], "github_reviewed": true, "github_reviewed_at": "2021-08-23T19:20:13Z", "nvd_published_at": "2021-08-12T21:15:00Z", "severity": "MODERATE" }, "details": "### Impact\nThe implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value.\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QuantizeAndDequantizeV4Grad(\n gradients=[1.0,2.0],\n input=[1.0,1.0],\n input_min=[0.0],\n input_max=[10.0],\n axis=-100)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer.\n\n### Patches\nWe have patched the issue in GitHub commit [96f364a1ca3009f98980021c4b32be5fdcca33a1](https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1).\n\nThe fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, 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-9w2p-5mgw-p94c", "modified": "2024-11-13T16:05:10Z", "published": "2021-08-25T14:43:37Z", "references": [ { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9w2p-5mgw-p94c" }, { "type": "ADVISORY", "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37645" }, { "type": "WEB", "url": "https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-558.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-756.yaml" }, { "type": "WEB", "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-267.yaml" }, { "type": "PACKAGE", "url": "https://github.com/tensorflow/tensorflow" } ], "schema_version": "1.4.0", "severity": [ { "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H", "type": "CVSS_V3" }, { "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N", "type": "CVSS_V4" } ], "summary": "Integer overflow due to conversion to unsigned" }
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.