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CNVD-2021-13933

Vulnerability from cnvd - Published: 2021-03-02
VLAI
Title
libcaca缓冲区溢出漏洞
Description
libcaca是一个将图像转换为彩色ASCII art的软件库。 libcaca v0.99.beta19中的libcaca/caca/canvas.c中的caca_resize函数存在缓冲区溢出漏洞。攻击者可利用该漏洞在用户上下文中执行任意代码。
Severity
Formal description

厂商尚未提供漏洞修复方案,请关注厂商主页更新: https://bugzilla.redhat.com/show_bug.cgi?id=1928437

Reference
https://nvd.nist.gov/vuln/detail/CVE-2021-3410
Impacted products
Name
libcaca libcaca v0.99.beta19
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2021-3410",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2021-3410"
    }
  },
  "description": "libcaca\u662f\u4e00\u4e2a\u5c06\u56fe\u50cf\u8f6c\u6362\u4e3a\u5f69\u8272ASCII art\u7684\u8f6f\u4ef6\u5e93\u3002\n\nlibcaca v0.99.beta19\u4e2d\u7684libcaca/caca/canvas.c\u4e2d\u7684caca_resize\u51fd\u6570\u5b58\u5728\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u5728\u7528\u6237\u4e0a\u4e0b\u6587\u4e2d\u6267\u884c\u4efb\u610f\u4ee3\u7801\u3002",
  "formalWay": "\u5382\u5546\u5c1a\u672a\u63d0\u4f9b\u6f0f\u6d1e\u4fee\u590d\u65b9\u6848\uff0c\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u66f4\u65b0\uff1a\r\nhttps://bugzilla.redhat.com/show_bug.cgi?id=1928437",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2021-13933",
  "openTime": "2021-03-02",
  "products": {
    "product": "libcaca libcaca v0.99.beta19"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2021-3410",
  "serverity": "\u4e2d",
  "submitTime": "2021-02-24",
  "title": "libcaca\u7f13\u51b2\u533a\u6ea2\u51fa\u6f0f\u6d1e"
}



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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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Nomenclature

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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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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.


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