CNVD-2016-00139

Vulnerability from cnvd - Published: 2016-01-11
VLAI
Title
InspIRCd 'src/dns.cpp'拒绝服务漏洞
Description
InspIRCd是一款可扩展的模块化的基于C++编写的用于Linux,BSD,Windows和Mac OS X系统中的互联网中继聊天(IRC)服务器。 InspIRCd中存在拒绝服务漏洞。攻击者可利用该漏洞使应用程序崩溃,拒绝服务合法用户。
Severity
Patch Name
InspIRCd 'src/dns.cpp'拒绝服务漏洞的补丁
Patch Description
InspIRCd是一款可扩展的模块化的基于C++编写的用于Linux,BSD,Windows和Mac OS X系统中的互联网中继聊天(IRC)服务器。 InspIRCd中存在拒绝服务漏洞。攻击者可利用该漏洞使应用程序崩溃,拒绝服务合法用户。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

目前厂商已经发布了升级补丁以修复此安全问题,详情请关注厂商主页: http://www.inspircd.org/

Reference
http://www.securityfocus.com/bid/79722
Impacted products
Name
InspIRCd InspIRCd
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "79722"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2015-8702"
    }
  },
  "description": "InspIRCd\u662f\u4e00\u6b3e\u53ef\u6269\u5c55\u7684\u6a21\u5757\u5316\u7684\u57fa\u4e8eC++\u7f16\u5199\u7684\u7528\u4e8eLinux\uff0cBSD\uff0cWindows\u548cMac OS X\u7cfb\u7edf\u4e2d\u7684\u4e92\u8054\u7f51\u4e2d\u7ee7\u804a\u5929\uff08IRC\uff09\u670d\u52a1\u5668\u3002\r\n\r\nInspIRCd\u4e2d\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4f7f\u5e94\u7528\u7a0b\u5e8f\u5d29\u6e83\uff0c\u62d2\u7edd\u670d\u52a1\u5408\u6cd5\u7528\u6237\u3002",
  "discovererName": "Mark Felder",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u7ecf\u53d1\u5e03\u4e86\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6b64\u5b89\u5168\u95ee\u9898\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttp://www.inspircd.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2016-00139",
  "openTime": "2016-01-11",
  "patchDescription": "InspIRCd\u662f\u4e00\u6b3e\u53ef\u6269\u5c55\u7684\u6a21\u5757\u5316\u7684\u57fa\u4e8eC++\u7f16\u5199\u7684\u7528\u4e8eLinux\uff0cBSD\uff0cWindows\u548cMac OS X\u7cfb\u7edf\u4e2d\u7684\u4e92\u8054\u7f51\u4e2d\u7ee7\u804a\u5929\uff08IRC\uff09\u670d\u52a1\u5668\u3002\r\n\r\nInspIRCd\u4e2d\u5b58\u5728\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u4f7f\u5e94\u7528\u7a0b\u5e8f\u5d29\u6e83\uff0c\u62d2\u7edd\u670d\u52a1\u5408\u6cd5\u7528\u6237\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": "InspIRCd \u0027src/dns.cpp\u0027\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "InspIRCd InspIRCd"
  },
  "referenceLink": "http://www.securityfocus.com/bid/79722",
  "serverity": "\u4e2d",
  "submitTime": "2016-01-08",
  "title": "InspIRCd \u0027src/dns.cpp\u0027\u62d2\u7edd\u670d\u52a1\u6f0f\u6d1e"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

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.


Loading…