Vulnerability-Lookup

CNVD-2021-64540

Vulnerability from cnvd - Published: 2021-08-24

Title

Google TensorFlow代码问题漏洞（CNVD-2021-64540）

Description

Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 Google TensorFlow存在安全漏洞，攻击者可利用漏洞通过在所有不需要广播的二进制\"cwise\"操作中绑定对空指针的引用来导致未定义的行为。

Severity

中

Patch Name

Google TensorFlow代码问题漏洞（CNVD-2021-64540）的补丁

Patch Description

Google TensorFlow是美国谷歌（Google）公司的一套用于机器学习的端到端开源平台。 Google TensorFlow存在安全漏洞，攻击者可利用漏洞通过在所有不需要广播的二进制\"cwise\"操作中绑定对空指针的引用来导致未定义的行为。目前，供应商发布了安全公告及相关补丁信息，修复了此漏洞。

Formal description

目前厂商已发布升级补丁以修复漏洞，补丁获取链接： https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q3g3-h9r4-prrc

Reference

https://nvd.nist.gov/vuln/detail/CVE-2021-37659

Impacted products

Name
['Google TensorFlow 2.5.1', 'Google TensorFlow 2.4.3', 'Google TensorFlow 2.3.4']

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2021-37659"
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  "number": "CNVD-2021-64540",
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}

CVE-2021-37659 (GCVE-0-2021-37659)

Vulnerability from cvelistv5 – Published: 2021-08-12 20:25 – Updated: 2024-08-04 01:23

Title

Out of bounds read via null pointer dereference in TensorFlow

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all binary cwise operations that don't require broadcasting (e.g., gradients of binary cwise operations). The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/cwise_ops_common.h#L264) assumes that the two inputs have exactly the same number of elements but does not check that. Hence, when the eigen functor executes it triggers heap OOB reads and undefined behavior due to binding to nullptr. We have patched the issue in GitHub commit 93f428fd1768df147171ed674fee1fc5ab8309ec. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Severity

7.3 (High)


                        
                          CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H

CWE

CWE-476 - NULL Pointer Dereference
CWE-125 - Out-of-bounds Read

Assigner

GitHub_M CNA under the mitre root

CNA scorecard C 72/100 over 7658 records in the last 180 days details

References

2 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/9…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: >= 2.5.0, < 2.5.1 Affected: >= 2.4.0, < 2.4.3 Affected: < 2.3.4

Show details on NVD website

JSON

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Sightings

Author	Source	Type	Date	Other

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.

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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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