Vulnerability-Lookup

GHSA-8QHG-C9H2-G6RJ

Vulnerability from github – Published: 2022-05-13 01:31 – Updated: 2024-07-23 21:31

Details

Check_MK before 1.2.8p26 mishandles certain errors within the failed-login save feature because of a race condition, which allows remote attackers to obtain sensitive user information by reading a GUI crash report.

Severity

5.9 (Medium)


                  
                    CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N

Show details on source website

JSON

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{
  "affected": [],
  "aliases": [
    "CVE-2017-14955"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-10-02T01:29:00Z",
    "severity": "MODERATE"
  },
  "details": "Check_MK before 1.2.8p26 mishandles certain errors within the failed-login save feature because of a race condition, which allows remote attackers to obtain sensitive user information by reading a GUI crash report.",
  "id": "GHSA-8qhg-c9h2-g6rj",
  "modified": "2024-07-23T21:31:31Z",
  "published": "2022-05-13T01:31:06Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-14955"
    },
    {
      "type": "WEB",
      "url": "https://mathias-kettner.de/check_mk_werks.php?werk_id=5208\u0026HTML=yes"
    },
    {
      "type": "WEB",
      "url": "https://www.exploit-db.com/exploits/43021"
    },
    {
      "type": "WEB",
      "url": "http://mathias-kettner.com/check_mk_werks.php?edition_id=raw\u0026branch=1.2.8"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2017-14955 (GCVE-0-2017-14955)

Vulnerability from cvelistv5 – Published: 2017-10-01 05:00 – Updated: 2024-08-05 19:42

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre CNA under the mitre root

CNA scorecard E 28/100 over 2298 records in the last 180 days details

References

3 references

URL	Tags
https://www.exploit-db.com/exploits/43021/	exploitx_refsource_EXPLOIT-DB
http://mathias-kettner.com/check_mk_werks.php?edi…	x_refsource_CONFIRM
https://mathias-kettner.de/check_mk_werks.php?wer…	x_refsource_CONFIRM

Date Public

2017-10-01 00:00

Show details on NVD website

JSON

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          "dateUpdated": "2024-08-05T19:42:22.360Z",
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            ],
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          },
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            ],
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          },
          {
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            "url": "https://mathias-kettner.de/check_mk_werks.php?werk_id=5208\u0026HTML=yes"
          }
        ],
        "title": "CVE Program Container"
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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.

Vulnerability timeline

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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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