Vulnerability-Lookup

CNVD-2019-23349

Vulnerability from cnvd - Published: 2019-07-19

Title

libnmap XML注入漏洞

Description

libnmap是一款用于操作nmap（网络探测和安全扫描程序）的python工具包。 libnmap 0.6.3之前版本中对MXL的解析存在安全漏洞。攻击者可借助特制的payload利用该漏洞造成拒绝服务。

Severity

中

Patch Name

libnmap XML注入漏洞的补丁

Patch Description

libnmap是一款用于操作nmap（网络探测和安全扫描程序）的python工具包。 libnmap 0.6.3之前版本中对MXL的解析存在安全漏洞。攻击者可借助特制的payload利用该漏洞造成拒绝服务。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

目前厂商已发布升级补丁以修复漏洞，详情请关注厂商主页： https://libnmap.readthedocs.org/

Reference

https://nvd.nist.gov/vuln/detail/CVE-2019-1010017

Impacted products

Name
libnmap libnmap <0.6.3

Show details on source website

JSON

To clipboard

{
  "cves": {
    "cve": {
      "cveNumber": "CVE-2019-1010017",
      "cveUrl": "https://nvd.nist.gov/vuln/detail/CVE-2019-1010017"
    }
  },
  "description": "libnmap\u662f\u4e00\u6b3e\u7528\u4e8e\u64cd\u4f5cnmap\uff08\u7f51\u7edc\u63a2\u6d4b\u548c\u5b89\u5168\u626b\u63cf\u7a0b\u5e8f\uff09\u7684python\u5de5\u5177\u5305\u3002\n\nlibnmap 0.6.3\u4e4b\u524d\u7248\u672c\u4e2d\u5bf9MXL\u7684\u89e3\u6790\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684payload\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u62d2\u7edd\u670d\u52a1\u3002",
  "discovererName": "unKnow",
  "formalWay": "\u76ee\u524d\u5382\u5546\u5df2\u53d1\u5e03\u5347\u7ea7\u8865\u4e01\u4ee5\u4fee\u590d\u6f0f\u6d1e\uff0c\u8be6\u60c5\u8bf7\u5173\u6ce8\u5382\u5546\u4e3b\u9875\uff1a\r\nhttps://libnmap.readthedocs.org/",
  "isEvent": "\u901a\u7528\u8f6f\u786c\u4ef6\u6f0f\u6d1e",
  "number": "CNVD-2019-23349",
  "openTime": "2019-07-19",
  "patchDescription": "libnmap\u662f\u4e00\u6b3e\u7528\u4e8e\u64cd\u4f5cnmap\uff08\u7f51\u7edc\u63a2\u6d4b\u548c\u5b89\u5168\u626b\u63cf\u7a0b\u5e8f\uff09\u7684python\u5de5\u5177\u5305\u3002\r\n\r\nlibnmap 0.6.3\u4e4b\u524d\u7248\u672c\u4e2d\u5bf9MXL\u7684\u89e3\u6790\u5b58\u5728\u5b89\u5168\u6f0f\u6d1e\u3002\u653b\u51fb\u8005\u53ef\u501f\u52a9\u7279\u5236\u7684payload\u5229\u7528\u8be5\u6f0f\u6d1e\u9020\u6210\u62d2\u7edd\u670d\u52a1\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": "libnmap XML\u6ce8\u5165\u6f0f\u6d1e\u7684\u8865\u4e01",
  "products": {
    "product": "libnmap libnmap \u003c0.6.3"
  },
  "referenceLink": "https://nvd.nist.gov/vuln/detail/CVE-2019-1010017",
  "serverity": "\u4e2d",
  "submitTime": "2019-07-15",
  "title": "libnmap XML\u6ce8\u5165\u6f0f\u6d1e"
}

CVE-2019-1010017 (GCVE-0-2019-1010017)

Vulnerability from cvelistv5 – Published: 2019-07-15 02:25 – Updated: 2024-08-05 03:07

Summary

libnmap < v0.6.3 is affected by: XML Injection. The impact is: Denial of service (DoS) by consuming resources. The component is: XML Parsing. The attack vector is: Specially crafted XML payload.

Severity

No CVSS data available.

CWE

XML Injection

Assigner

dwf Scorecard

References

1 reference

URL	Tags
https://github.com/savon-noir/python-libnmap/issues/87	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
libnmap	libnmap	Affected: < v0.6.3

Show details on NVD website

JSON

To clipboard

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          "dateUpdated": "2024-08-05T03:07:18.214Z",
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              "x_transferred"
            ],
            "url": "https://github.com/savon-noir/python-libnmap/issues/87"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "libnmap",
          "vendor": "libnmap",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c v0.6.3"
            }
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      ],
      "problemTypes": [
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          "descriptions": [
            {
              "description": "XML Injection",
              "lang": "en",
              "type": "text"
            }
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      ],
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        "dateUpdated": "2019-07-15T02:25:52.000Z",
        "orgId": "7556d962-6fb7-411e-85fa-6cd62f095ba8",
        "shortName": "dwf"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/savon-noir/python-libnmap/issues/87"
        }
      ],
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "cve-assign@distributedweaknessfiling.org",
          "ID": "CVE-2019-1010017",
          "STATE": "PUBLIC"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "libnmap",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "\u003c v0.6.3"
                          }
                        ]
                      }
                    }
                  ]
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                "vendor_name": "libnmap"
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              "description": [
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                  "lang": "eng",
                  "value": "XML Injection"
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        "references": {
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              "refsource": "MISC",
              "url": "https://github.com/savon-noir/python-libnmap/issues/87"
            }
          ]
        }
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  },
  "cveMetadata": {
    "assignerOrgId": "7556d962-6fb7-411e-85fa-6cd62f095ba8",
    "assignerShortName": "dwf",
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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.

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.

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CNVD-2019-23349

CVE-2019-1010017 (GCVE-0-2019-1010017)

Tags

Sightings

Nomenclature

Related by attack behaviour