GHSA-H9PX-9VQG-222H
Vulnerability from github – Published: 2021-05-21 14:23 – Updated: 2024-10-31 20:51Impact
An attacker can read data outside of bounds of heap allocated buffer in tf.raw_ops.QuantizeAndDequantizeV3:
import tensorflow as tf
tf.raw_ops.QuantizeAndDequantizeV3(
input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30],
signed_input=False, range_given=False, narrow_range=False, axis=3)
This is because the implementation does not validate the value of user supplied axis attribute before using it to index in the array backing the input argument:
const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);
Patches
We have patched the issue in GitHub commit 99085e8ff02c3763a0ec2263e44daec416f6a387.
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 Aivul Team from Qihoo 360.
{
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],
"aliases": [
"CVE-2021-29553"
],
"database_specific": {
"cwe_ids": [
"CWE-125"
],
"github_reviewed": true,
"github_reviewed_at": "2021-05-18T20:59:57Z",
"nvd_published_at": "2021-05-14T20:15:00Z",
"severity": "LOW"
},
"details": "### Impact\nAn attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QuantizeAndDequantizeV3(\n input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30],\n signed_input=False, range_given=False, narrow_range=False, axis=3)\n``` \n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument:\n\n```cc\nconst int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);\n```\n\n### Patches\nWe have patched the issue in GitHub commit [99085e8ff02c3763a0ec2263e44daec416f6a387](https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387).\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 Aivul Team from Qihoo 360.",
"id": "GHSA-h9px-9vqg-222h",
"modified": "2024-10-31T20:51:10Z",
"published": "2021-05-21T14:23:51Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29553"
},
{
"type": "WEB",
"url": "https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-481.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-679.yaml"
},
{
"type": "WEB",
"url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-190.yaml"
},
{
"type": "PACKAGE",
"url": "https://github.com/tensorflow/tensorflow"
}
],
"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": "Heap OOB in `QuantizeAndDequantizeV3`"
}
Sightings
| Author | Source | Type | Date |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.