Vulnerability-Lookup

CNVD-2022-20173

Vulnerability from cnvd - Published: 2022-03-17

Title

Imagemagick Studio ImageMagick缓冲区溢出漏洞（CNVD-2022-20173）

Description

Imagemagick Studio ImageMagick是美国ImageMagick Studio（Imagemagick Studio）公司的一套开源的图像处理软件。该软件可读取、转换或写入多种格式的图片。 ImageMagick存在缓冲区溢出漏洞，该漏洞源于在编码器tiff.c中的ReadTIFFImage()中发现了一个基于堆的缓冲区溢出漏洞。此问题是由于像素数组大小设置错误，可能导致崩溃和分割故障。目前没有详细的漏洞细节提供。

Severity

中

Patch Name

Imagemagick Studio ImageMagick缓冲区溢出漏洞（CNVD-2022-20173）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/ImageMagick/ImageMagick/commit/930ff0d1a9bc42925a7856e9ea53f5fc9f318bf3

Reference

https://nvd.nist.gov/vuln/detail/CVE-2021-3610

Impacted products

Name
ImageMagick ImageMagick <7.0.11-14

Show details on source website

JSON

To clipboard

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    "cve": {
      "cveNumber": "CVE-2021-3610"
    }
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  "number": "CNVD-2022-20173",
  "openTime": "2022-03-17",
  "patchDescription": "Imagemagick Studio ImageMagick\u662f\u7f8e\u56fdImageMagick Studio\uff08Imagemagick Studio\uff09\u516c\u53f8\u7684\u4e00\u5957\u5f00\u6e90\u7684\u56fe\u50cf\u5904\u7406\u8f6f\u4ef6\u3002\u8be5\u8f6f\u4ef6\u53ef\u8bfb\u53d6\u3001\u8f6c\u6362\u6216\u5199\u5165\u591a\u79cd\u683c\u5f0f\u7684\u56fe\u7247\u3002\r\n\r\nImageMagick\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u5728\u7f16\u7801\u5668tiff.c\u4e2d\u7684ReadTIFFImage()\u4e2d\u53d1\u73b0\u4e86\u4e00\u4e2a\u57fa\u4e8e\u5806\u7684\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u6b64\u95ee\u9898\u662f\u7531\u4e8e\u50cf\u7d20\u6570\u7ec4\u5927\u5c0f\u8bbe\u7f6e\u9519\u8bef\uff0c\u53ef\u80fd\u5bfc\u81f4\u5d29\u6e83\u548c\u5206\u5272\u6545\u969c\u3002 \u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u7684\u6f0f\u6d1e\u7ec6\u8282\u63d0\u4f9b\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": "Imagemagick Studio ImageMagick\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-20173\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "ImageMagick ImageMagick \u003c7.0.11-14"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-3610",
  "serverity": "\u4e2d",
  "submitTime": "2022-02-25",
  "title": "Imagemagick Studio ImageMagick\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2022-20173\uff09"
}

CVE-2021-3610 (GCVE-0-2021-3610)

Vulnerability from cvelistv5 – Published: 2022-02-24 00:00 – Updated: 2026-01-26 16:39

Summary

A heap-based buffer overflow vulnerability was found in ImageMagick in versions prior to 7.0.11-14 in ReadTIFFImage() in coders/tiff.c. This issue is due to an incorrect setting of the pixel array size, which can lead to a crash and segmentation fault.

Severity

No CVSS data available.

CWE

CWE-125

Assigner

redhat redhat root

References

5 references

URL	Tags
https://bugzilla.redhat.com/show_bug.cgi?id=1973689
https://github.com/ImageMagick/ImageMagick/commit…
http://www.openwall.com/lists/oss-security/2023/05/29/4	mailing-list
http://www.openwall.com/lists/oss-security/2023/06/05/1	mailing-list
https://github.com/fuzzing2026/CVE-PoCs/tree/main…

Impacted products

1 product

Vendor	Product	Version
n/a	ImageMagick	Affected: ImageMagick 7.0.11-14

Show details on NVD website

JSON

To clipboard

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    "cna": {
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          "vendor": "n/a",
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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.