Vulnerability-Lookup

GHSA-WXCR-9P2R-C64C

Vulnerability from github – Published: 2022-05-14 01:10 – Updated: 2022-05-14 01:10

Details

In F5 BIG-IP APM software version 13.0.0 and 12.1.2, under rare conditions, the BIG-IP APM system appends log details when responding to client requests. Details in the log file can vary; customers running debug mode logging with BIG-IP APM are at highest risk.

Severity

5.9 (Medium)


                  
                    CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N

Show details on source website

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{
  "affected": [],
  "aliases": [
    "CVE-2017-6139"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-532"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2017-12-21T17:29:00Z",
    "severity": "MODERATE"
  },
  "details": "In F5 BIG-IP APM software version 13.0.0 and 12.1.2, under rare conditions, the BIG-IP APM system appends log details when responding to client requests. Details in the log file can vary; customers running debug mode logging with BIG-IP APM are at highest risk.",
  "id": "GHSA-wxcr-9p2r-c64c",
  "modified": "2022-05-14T01:10:43Z",
  "published": "2022-05-14T01:10:43Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2017-6139"
    },
    {
      "type": "WEB",
      "url": "https://support.f5.com/csp/article/K45432295"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/106186"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1040055"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2017-6139 (GCVE-0-2017-6139)

Vulnerability from cvelistv5 – Published: 2017-12-21 17:00 – Updated: 2024-09-16 18:23

Summary

Severity

No CVSS data available.

CWE

Information Leakage

Assigner

f5 mitre root

References

3 references

URL	Tags
https://support.f5.com/csp/article/K45432295	x_refsource_CONFIRM
http://www.securitytracker.com/id/1040055	vdb-entryx_refsource_SECTRACK
http://www.securityfocus.com/bid/106186	vdb-entryx_refsource_BID

Impacted products

1 product

Vendor	Product	Version
F5 Networks, Inc.	BIG-IP APM	Affected: 13.0.0 Affected: 12.1.2

Date Public

2017-12-20 00:00

Show details on NVD website

JSON

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        "references": [
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            "url": "https://support.f5.com/csp/article/K45432295"
          },
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            "tags": [
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        ],
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    ],
    "cna": {
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          "vendor": "F5 Networks, Inc.",
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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.