CNVD-2017-36183

Vulnerability from cnvd - Published: 2017-12-05
VLAI
Title
Catalyst Mahara信息泄露漏洞
Description
Catalyst Mahara是新西兰Catalyst IT公司的一套社交网络系统。该系统包含博客、履历表生成器、文件管理器等。 Catalyst Mahara中存在安全漏洞,该漏洞源于程序将密码以明文的形式储存在event_log表单中。攻击者可利用该漏洞获取信息。
Severity
低
Patch Name
Catalyst Mahara信息泄露漏洞的补丁
Patch Description
Catalyst Mahara是新西兰Catalyst IT公司的一套社交网络系统。该系统包含博客、履历表生成器、文件管理器等。 Catalyst Mahara中存在安全漏洞,该漏洞源于程序将密码以明文的形式储存在event_log表单中。攻击者可利用该漏洞获取信息。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

厂商已发布漏洞修复程序,请及时关注更新: https://bugs.launchpad.net/mahara/+bug/1692749

Reference
https://nvd.nist.gov/vuln/detail/CVE-2017-1000157
Impacted products
Name
['Catalyst IT Mahara 15.04 (<15.04.13)', 'Catalyst IT Mahara 16.04 (<16.04.7)', 'Catalyst IT Mahara 16.10 (<16.10.4)', 'Catalyst IT Mahara 17.04 (<17.04.2 )']
Show details on source website

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2017-1000157"
    }
  },
  "description": "Catalyst Mahara\u662f\u65b0\u897f\u5170Catalyst IT\u516c\u53f8\u7684\u4e00\u5957\u793e\u4ea4\u7f51\u7edc\u7cfb\u7edf\u3002\u8be5\u7cfb\u7edf\u5305\u542b\u535a\u5ba2\u3001\u5c65\u5386\u8868\u751f\u6210\u5668\u3001\u6587\u4ef6\u7ba1\u7406\u5668\u7b49\u3002\r\n\r\nCatalyst Mahara\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u5c06\u5bc6\u7801\u4ee5\u660e\u6587\u7684\u5f62\u5f0f\u50a8\u5b58\u5728event_log\u8868\u5355\u4e2d\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u4fe1\u606f\u3002",
  "discovererName": "Robert Lyon",
  "formalWay": "\u5382\u5546\u5df2\u53d1\u5e03\u6f0f\u6d1e\u4fee\u590d\u7a0b\u5e8f\uff0c\u8bf7\u53ca\u65f6\u5173\u6ce8\u66f4\u65b0\uff1a\r\nhttps://bugs.launchpad.net/mahara/+bug/1692749",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2017-36183",
  "openTime": "2017-12-05",
  "patchDescription": "Catalyst Mahara\u662f\u65b0\u897f\u5170Catalyst IT\u516c\u53f8\u7684\u4e00\u5957\u793e\u4ea4\u7f51\u7edc\u7cfb\u7edf\u3002\u8be5\u7cfb\u7edf\u5305\u542b\u535a\u5ba2\u3001\u5c65\u5386\u8868\u751f\u6210\u5668\u3001\u6587\u4ef6\u7ba1\u7406\u5668\u7b49\u3002\r\n\r\nCatalyst Mahara\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\uff0c\u8be5\u6f0f\u6d1e\u6e90\u4e8e\u7a0b\u5e8f\u5c06\u5bc6\u7801\u4ee5\u660e\u6587\u7684\u5f62\u5f0f\u50a8\u5b58\u5728event_log\u8868\u5355\u4e2d\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u83b7\u53d6\u4fe1\u606f\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": "Catalyst Mahara\u4fe1\u606f\u6cc4\u9732\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": [
      "Catalyst IT Mahara 15.04 (\u003c15.04.13)",
      "Catalyst IT Mahara 16.04 (\u003c16.04.7)",
      "Catalyst IT Mahara 16.10 (\u003c16.10.4)",
      "Catalyst IT Mahara 17.04 (\u003c17.04.2 )"
    ]
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2017-1000157",
  "serverity": "\u4f4e",
  "submitTime": "2017-11-06",
  "title": "Catalyst Mahara\u4fe1\u606f\u6cc4\u9732\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

  • 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.
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  • 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.

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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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