Vulnerability-Lookup

CNVD-2021-87034

Vulnerability from cnvd - Published: 2021-11-12

Title

Google TensorFlow缓冲区溢出漏洞（CNVD-2021-87034）

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存在缓冲区溢出漏洞，该漏洞源于 ImmutableConst 操作可以被诱骗读取任意内存内容。这是因为 TensorFlow 字符串类（tstring）对内存映射字符串有一个特殊情况，但操作本身不提供对这种数据类型的任何支持。目前没有详细的漏洞细节提供。

Severity

低

Patch Name

Google TensorFlow缓冲区溢出漏洞（CNVD-2021-87034）的补丁

Patch Description

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-j8c8-67vp-6mx7

Reference

https://github.com/tensorflow/tensorflow/commit/1cb6bb6c2a6019417c9adaf9e6843ba75ee2580b

Impacted products

Name
Google TensorFlow

Show details on source website

JSON

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CVE-2021-41227 (GCVE-0-2021-41227)

Vulnerability from cvelistv5 – Published: 2021-11-05 22:30 – Updated: 2024-08-04 03:08

Title

Arbitrary memory read in `ImmutableConst`

Summary

TensorFlow is an open source platform for machine learning. In affected versions the `ImmutableConst` operation in TensorFlow can be tricked into reading arbitrary memory contents. This is because the `tstring` TensorFlow string class has a special case for memory mapped strings but the operation itself does not offer any support for this datatype. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Severity

6.6 (Medium)


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

CWE

CWE-125 - Out-of-bounds Read

Assigner

GitHub_M mitre root

References

3 references

URL	Tags
https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
https://github.com/tensorflow/tensorflow/commit/1…	x_refsource_MISC
https://github.com/tensorflow/tensorflow/commit/3…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
tensorflow	tensorflow	Affected: >= 2.6.0, < 2.6.1 Affected: >= 2.5.0, < 2.5.2 Affected: < 2.4.4

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.

Detection rules are retrieved from Rulezet.

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.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.