Vulnerability-Lookup

CNVD-2020-35399

Vulnerability from cnvd - Published: 2020-06-30

Title

Google TensorFlow缓冲区溢出漏洞（CNVD-2020-35399）

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 1.7.0之前版本中的core/kernels/decode_bmp_op.cc文件的BMP decoder的DecodeBmp功能存在缓冲区溢出漏洞。攻击者可利用该漏洞获取进程内存的内容。

Severity

中

Patch Name

Google TensorFlow缓冲区溢出漏洞（CNVD-2020-35399）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/commit/49f73c55d56edffebde4bca4a407ad69c1cae433

Reference

https://nvd.nist.gov/vuln/detail/CVE-2018-21233

Impacted products

Name
Google TensorFlow <1.7.0

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2018-21233"
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  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2020-35399",
  "openTime": "2020-06-30",
  "patchDescription": "Google TensorFlow\u662f\u7f8e\u56fd\u8c37\u6b4c\uff08Google\uff09\u516c\u53f8\u7684\u4e00\u5957\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u7aef\u5230\u7aef\u5f00\u6e90\u5e73\u53f0\u3002\r\n\r\nGoogle TensorFlow 1.7.0\u4e4b\u524d\u7248\u672c\u4e2d\u7684core/kernels/decode_bmp_op.cc\u6587\u4ef6\u7684BMP decoder\u7684DecodeBmp\u529f\u80fd\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u8fdb\u7a0b\u5185\u5b58\u7684\u5185\u5bb9\u3002\u76ee\u524d\uff0c\u4f9b\u5e94\u5546\u53d1\u5e03\u4e86\u5b89\u5168\u516c\u544a\u53ca\u76f8\u5173\u8865\u4e01\u4fe1\u606f\uff0c\u4fee\u590d\u4e86\u6b64\u6f0f\u6d1e\u3002",
  "patchName": "Google TensorFlow\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2020-35399\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "Google TensorFlow \u003c1.7.0"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2018-21233",
  "serverity": "\u4e2d",
  "submitTime": "2020-05-06",
  "title": "Google TensorFlow\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2020-35399\uff09"
}

CVE-2018-21233 (GCVE-0-2018-21233)

Vulnerability from cvelistv5 – Published: 2020-05-04 14:12 – Updated: 2024-08-05 12:26

Summary

TensorFlow before 1.7.0 has an integer overflow that causes an out-of-bounds read, possibly causing disclosure of the contents of process memory. This occurs in the DecodeBmp feature of the BMP decoder in core/kernels/decode_bmp_op.cc.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://github.com/tensorflow/tensorflow/blob/mas…	x_refsource_MISC
https://github.com/tensorflow/tensorflow/commit/4…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-05T12:26:39.467Z",
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          }
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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.

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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.

Action not permitted

CNVD-2020-35399

CVE-2018-21233 (GCVE-0-2018-21233)

Tags

Sightings

Nomenclature

Related by attack behaviour