CNVD-2016-02220

Vulnerability from cnvd - Published: 2016-04-15
VLAI
Title
cronic任意文件写入漏洞
Description
cronic是软件开发者Daniel Lange所负责维护的一个用于包装cron作业以防止多余的电子邮件发送的shell脚本。 cronic中存在任意文件写入漏洞,攻击者可通过创建符号链接‘/tmp/cronic.out.PID -> /etc/fstab’利用该漏洞写入任意文件。
Severity
Formal description

目前厂商暂未发布修复措施解决此安全问题,建议使用此软件的用户随时关注厂商主页或参考网址以获取解决办法: http://habilis.net/cronic/

Reference
http://habilis.net/cronic/
Impacted products
Name
cronic cronic
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2016-3992"
    }
  },
  "description": "cronic\u662f\u8f6f\u4ef6\u5f00\u53d1\u8005Daniel Lange\u6240\u8d1f\u8d23\u7ef4\u62a4\u7684\u4e00\u4e2a\u7528\u4e8e\u5305\u88c5cron\u4f5c\u4e1a\u4ee5\u9632\u6b62\u591a\u4f59\u7684\u7535\u5b50\u90ae\u4ef6\u53d1\u9001\u7684shell\u811a\u672c\u3002\r\n\r\ncronic\u4e2d\u5b58\u5728\u4efb\u610f\u6587\u4ef6\u5199\u5165\u6f0f\u6d1e\uff0c\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u521b\u5efa\u7b26\u53f7\u94fe\u63a5\u0026lsquo;/tmp/cronic.out.PID -\u0026gt; /etc/fstab\u0026rsquo;\u5229\u7528\u8be5\u6f0f\u6d1e\u5199\u5165\u4efb\u610f\u6587\u4ef6\u3002",
  "discovererName": "Dmitry Nezhevenko",
  "formalWay": "\u76ee\u524d\u5382\u5546\u6682\u672a\u53d1\u5e03\u4fee\u590d\u63aa\u65bd\u89e3\u51b3\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u5efa\u8bae\u4f7f\u7528\u6b64\u8f6f\u4ef6\u7684\u7528\u6237\u968f\u65f6\u5173\u6ce8\u5382\u5546\u4e3b\u9875\u6216\u53c2\u8003\u7f51\u5740\u4ee5\u83b7\u53d6\u89e3\u51b3\u529e\u6cd5\uff1a\r\nhttp://habilis.net/cronic/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-02220",
  "openTime": "2016-04-15",
  "products": {
    "product": "cronic cronic"
  },
  "referenceLink": "http://habilis.net/cronic/",
  "serverity": "\u4e2d",
  "submitTime": "2016-04-13",
  "title": "cronic\u4efb\u610f\u6587\u4ef6\u5199\u5165\u6f0f\u6d1e"
}



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Sightings

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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
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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.


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