CNVD-2015-01655

Vulnerability from cnvd - Published: 2015-03-13
VLAI
Title
Agilent Technologies Feature Extraction AnnotationX.AnnList.1 ActiveX控件任意代码执行漏洞
Description
Agilent Technologies Feature Extraction是美国安捷伦(Agilent Technologies)公司的一套用于自动读取并处理多个原始芯片的图像文件的特征提取软件。 Agilent Technologies Feature Extraction的AnnotationX.AnnList.1 ActiveX控件中存在安全漏洞。远程攻击者可通过‘Insert’函数中特制的‘object’参数利用该漏洞执行任意代码。
Severity
高
Formal description

目前没有详细解决方案提供: http://www.webgateinc.com/wgi/eng/

Reference
http://www.zerodayinitiative.com/advisories/ZDI-15-053/
Impacted products
Name
Agilent Technologies Feature Extraction
Show details on source website

{
  "bids": {
    "bid": {
      "bidNumber": "72840"
    }
  },
  "cves": {
    "cve": {
      "cveNumber": "CVE-2015-2092"
    }
  },
  "description": "Agilent Technologies Feature Extraction\u662f\u7f8e\u56fd\u5b89\u6377\u4f26\uff08Agilent Technologies\uff09\u516c\u53f8\u7684\u4e00\u5957\u7528\u4e8e\u81ea\u52a8\u8bfb\u53d6\u5e76\u5904\u7406\u591a\u4e2a\u539f\u59cb\u82af\u7247\u7684\u56fe\u50cf\u6587\u4ef6\u7684\u7279\u5f81\u63d0\u53d6\u8f6f\u4ef6\u3002\r\n\r\nAgilent Technologies Feature Extraction\u7684AnnotationX.AnnList.1 ActiveX\u63a7\u4ef6\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u8fdc\u7a0b\u653b\u51fb\u8005\u53ef\u901a\u8fc7\u2018Insert\u2019\u51fd\u6570\u4e2d\u7279\u5236\u7684\u2018object\u2019\u53c2\u6570\u5229\u7528\u8be5\u6f0f\u6d1e\u6267\u884c\u4efb\u610f\u4ee3\u7801\u3002",
  "discovererName": "rgod",
  "formalWay": "\u76ee\u524d\u6ca1\u6709\u8be6\u7ec6\u89e3\u51b3\u65b9\u6848\u63d0\u4f9b\uff1a\r\nhttp://www.webgateinc.com/wgi/eng/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2015-01655",
  "openTime": "2015-03-13",
  "products": {
    "product": "Agilent Technologies Feature Extraction"
  },
  "referenceLink": "http://www.zerodayinitiative.com/advisories/ZDI-15-053/",
  "serverity": "\u9ad8",
  "submitTime": "2015-03-11",
  "title": "Agilent Technologies Feature Extraction AnnotationX.AnnList.1 ActiveX\u63a7\u4ef6\u4efb\u610f\u4ee3\u7801\u6267\u884c\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…

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…