Vulnerability-Lookup

CNVD-2019-26829

Vulnerability from cnvd - Published: 2019-08-12

Title

MSI installer for Python代码执行漏洞

Description

Python是Python软件基金会的一套开源的、面向对象的程序设计语言。该语言具有可扩展、支持模块和包、支持多种平台等特点。MSI installer for Python是一款基于Windows平台的Python安装程序。 MSI installer for Python 2.7.16及之前版本和3.5之前的3.x版本中存在安全漏洞。攻击者可利用该漏洞部署恶意代码。

Severity

高

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： https://www.python.org/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2019-13404

Impacted products

Name
['Python MSI installer for Python <=2.7.16', 'Python MSI installer for Python 3.*，<3.5']

Show details on source website

JSON

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{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2019-13404"
    }
  },
  "description": "Python\u662fPython\u8f6f\u4ef6\u57fa\u91d1\u4f1a\u7684\u4e00\u5957\u5f00\u6e90\u7684\u3001\u9762\u5411\u5bf9\u8c61\u7684\u7a0b\u5e8f\u8bbe\u8ba1\u8bed\u8a00\u3002\u8be5\u8bed\u8a00\u5177\u6709\u53ef\u6269\u5c55\u3001\u652f\u6301\u6a21\u5757\u548c\u5305\u3001\u652f\u6301\u591a\u79cd\u5e73\u53f0\u7b49\u7279\u70b9\u3002MSI installer for Python\u662f\u4e00\u6b3e\u57fa\u4e8eWindows\u5e73\u53f0\u7684Python\u5b89\u88c5\u7a0b\u5e8f\u3002\n\nMSI installer for Python 2.7.16\u53ca\u4e4b\u524d\u7248\u672c\u548c3.5\u4e4b\u524d\u76843.x\u7248\u672c\u4e2d\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u5229\u7528\u8be5\u6f0f\u6d1e\u90e8\u7f72\u6076\u610f\u4ee3\u7801\u3002",
  "discovererName": "unknwon",
  "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\nhttps://www.python.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-26829",
  "openTime": "2019-08-12",
  "products": {
    "product": [
      "Python MSI installer for Python \u003c=2.7.16",
      "Python MSI installer for Python 3.*\uff0c\u003c3.5"
    ]
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-13404",
  "serverity": "\u9ad8",
  "submitTime": "2019-07-09",
  "title": "MSI installer for Python\u4ee3\u7801\u6267\u884c\u6f0f\u6d1e"
}

CVE-2019-13404 (GCVE-0-2019-13404)

Vulnerability from cvelistv5 – Published: 2019-07-08 00:54 – Updated: 2024-08-04 23:49 Disputed

Summary

The MSI installer for Python through 2.7.16 on Windows defaults to the C:\Python27 directory, which makes it easier for local users to deploy Trojan horse code. (This also affects old 3.x releases before 3.5.) NOTE: the vendor's position is that it is the user's responsibility to ensure C:\Python27 access control or choose a different directory, because backwards compatibility requires that C:\Python27 remain the default for 2.7.x

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://docs.python.org/2/faq/windows.html	x_refsource_MISC

Show details on NVD website

JSON

To clipboard

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            ],
            "url": "https://docs.python.org/2/faq/windows.html"
          }
        ],
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      }
    ],
    "cna": {
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          "vendor": "n/a",
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              "status": "affected",
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      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "The MSI installer for Python through 2.7.16 on Windows defaults to the C:\\Python27 directory, which makes it easier for local users to deploy Trojan horse code. (This also affects old 3.x releases before 3.5.) NOTE: the vendor\u0027s position is that it is the user\u0027s responsibility to ensure C:\\Python27 access control or choose a different directory, because backwards compatibility requires that C:\\Python27 remain the default for 2.7.x"
        }
      ],
      "problemTypes": [
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            }
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        "dateUpdated": "2019-07-08T00:54:41.000Z",
        "orgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "shortName": "mitre"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://docs.python.org/2/faq/windows.html"
        }
      ],
      "tags": [
        "disputed"
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          "STATE": "PUBLIC"
        },
        "affects": {
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            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "n/a",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "n/a"
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        "description": {
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        "references": {
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  "cveMetadata": {
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}

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.

Detection rules are retrieved from Rulezet.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

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.