Vulnerability-Lookup

GHSA-JR9Q-CM32-5462

Vulnerability from github – Published: 2022-05-14 03:30 – Updated: 2022-05-14 03:30

Details

An issue was discovered in Heimdal PRO 2.2.190. As part of the scanning feature, a process called md.hs writes an executable called CS1.tmp to C:\windows\TEMP. Afterwards the executable is run. It is possible for an attacker to create the file first, let md.hs overwrite it, and then rewrite the file in the window between md.hs closing the file and executing it. This can be exploited via opportunistic locks and a high priority thread. The vulnerability is triggered when a scan starts. NOTE: any affected Heimdal products are completely unrelated to the Heimdal vendor of a Kerberos 5 product on the h5l.org web site.

Severity

7.0 (High)


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

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{
  "affected": [],
  "aliases": [
    "CVE-2018-5731"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-20"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2018-03-22T16:29:00Z",
    "severity": "HIGH"
  },
  "details": "An issue was discovered in Heimdal PRO 2.2.190. As part of the scanning feature, a process called md.hs writes an executable called CS1.tmp to C:\\windows\\TEMP. Afterwards the executable is run. It is possible for an attacker to create the file first, let md.hs overwrite it, and then rewrite the file in the window between md.hs closing the file and executing it. This can be exploited via opportunistic locks and a high priority thread. The vulnerability is triggered when a scan starts. NOTE: any affected Heimdal products are completely unrelated to the Heimdal vendor of a Kerberos 5 product on the h5l.org web site.",
  "id": "GHSA-jr9q-cm32-5462",
  "modified": "2022-05-14T03:30:14Z",
  "published": "2022-05-14T03:30:14Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2018-5731"
    },
    {
      "type": "WEB",
      "url": "https://improsec.com/blog/heimdal-advisory-2"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ]
}

CVE-2018-5731 (GCVE-0-2018-5731)

Vulnerability from cvelistv5 – Published: 2018-03-22 16:00 – Updated: 2024-08-05 05:40

Summary

Severity

No CVSS data available.

CWE

Assigner

mitre mitre root

References

1 reference

URL	Tags
https://improsec.com/blog/heimdal-advisory-2	x_refsource_MISC

Date Public

2018-03-22 00:00

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JSON

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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.