Vulnerability-Lookup

CNVD-2019-32484

Vulnerability from cnvd - Published: 2019-09-21

Title

ngiflib缓冲区溢出漏洞（CNVD-2019-32484）

Description

ngiflib是用C语言编写的GIF图片格式解码库。 ngiflib 0.4版本中的ngiflib.c文件的WritePixel()存在缓冲区溢出漏洞，攻击者可利用该漏洞导致缓冲区溢出或堆溢出。

Severity

低

Patch Name

ngiflib缓冲区溢出漏洞（CNVD-2019-32484）的补丁

Patch Description

ngiflib是用C语言编写的GIF图片格式解码库。 ngiflib 0.4版本中的ngiflib.c文件的WritePixel()存在缓冲区溢出漏洞，攻击者可利用该漏洞导致缓冲区溢出或堆溢出。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

厂商已发布了漏洞修复程序，请及时关注更新： https://github.com/miniupnp/ngiflib/commit/37d939a6f511d16d4c95678025c235fe62e6417a

Reference

https://nvd.nist.gov/vuln/detail/CVE-2019-16346

Impacted products

Name
MiniUPnP ngiflib 0.4

Show details on source website

JSON

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    "cve": {
      "cveNumber": "CVE-2019-16346",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2019-16346"
    }
  },
  "description": "ngiflib\u662f\u7528C\u8bed\u8a00\u7f16\u5199\u7684GIF\u56fe\u7247\u683c\u5f0f\u89e3\u7801\u5e93\u3002\n\nngiflib 0.4\u7248\u672c\u4e2d\u7684ngiflib.c\u6587\u4ef6\u7684WritePixel()\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u6216\u5806\u6ea2\u51fa\u3002",
  "discovererName": "Marsman1996",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u4e86\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://github.com/miniupnp/ngiflib/commit/37d939a6f511d16d4c95678025c235fe62e6417a",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-32484",
  "openTime": "2019-09-21",
  "patchDescription": "ngiflib\u662f\u7528C\u8bed\u8a00\u7f16\u5199\u7684GIF\u56fe\u7247\u683c\u5f0f\u89e3\u7801\u5e93\u3002\r\n\r\nngiflib 0.4\u7248\u672c\u4e2d\u7684ngiflib.c\u6587\u4ef6\u7684WritePixel()\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5bfc\u81f4\u7f13\u51b2\u533a\u6ea2\u51fa\u6216\u5806\u6ea2\u51fa\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": "ngiflib\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2019-32484\uff09\u7684\u8865\u4e01",
  "products": {
    "product": "MiniUPnP ngiflib 0.4"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-16346",
  "serverity": "\u4f4e",
  "submitTime": "2019-09-17",
  "title": "ngiflib\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\uff08CNVD-2019-32484\uff09"
}

CVE-2019-16346 (GCVE-0-2019-16346)

Vulnerability from cvelistv5 – Published: 2019-09-16 12:57 – Updated: 2024-08-05 01:10

Summary

ngiflib 0.4 has a heap-based buffer overflow in WritePixel() in ngiflib.c when called from DecodeGifImg, because deinterlacing for small pictures is mishandled.

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

2 references

URL	Tags
https://github.com/miniupnp/ngiflib/issues/11	x_refsource_MISC
https://github.com/miniupnp/ngiflib/commit/37d939…	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

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            "url": "https://github.com/miniupnp/ngiflib/commit/37d939a6f511d16d4c95678025c235fe62e6417a"
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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.