Vulnerability-Lookup

GHSA-7JMH-4C44-4PQC

Vulnerability from github – Published: 2022-05-14 01:03 – Updated: 2022-05-14 01:03

Details

The kernel-mode drivers in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 do not properly initialize function buffers, which allows local users to obtain sensitive information from kernel memory, and possibly bypass the ASLR protection mechanism, via a crafted application, aka "Microsoft Windows Kernel Memory Disclosure Vulnerability."

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{
  "affected": [],
  "aliases": [
    "CVE-2015-0077"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-200"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2015-03-11T10:59:00Z",
    "severity": "LOW"
  },
  "details": "The kernel-mode drivers in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 do not properly initialize function buffers, which allows local users to obtain sensitive information from kernel memory, and possibly bypass the ASLR protection mechanism, via a crafted application, aka \"Microsoft Windows Kernel Memory Disclosure Vulnerability.\"",
  "id": "GHSA-7jmh-4c44-4pqc",
  "modified": "2022-05-14T01:03:12Z",
  "published": "2022-05-14T01:03:12Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2015-0077"
    },
    {
      "type": "WEB",
      "url": "https://docs.microsoft.com/en-us/security-updates/securitybulletins/2015/ms15-023"
    },
    {
      "type": "WEB",
      "url": "http://www.securityfocus.com/bid/72897"
    },
    {
      "type": "WEB",
      "url": "http://www.securitytracker.com/id/1031897"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}

CVE-2015-0077 (GCVE-0-2015-0077)

Vulnerability from cvelistv5 – Published: 2015-03-11 10:00 – Updated: 2024-08-06 03:55

Summary

Severity

No CVSS data available.

CWE

Assigner

microsoft mitre root

References

3 references

URL	Tags
http://www.securityfocus.com/bid/72897	vdb-entryx_refsource_BID
http://www.securitytracker.com/id/1031897	vdb-entryx_refsource_SECTRACK
https://docs.microsoft.com/en-us/security-updates…	vendor-advisoryx_refsource_MS

Date Public

2015-03-10 00:00

Show details on NVD website

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          }
        ],
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    ],
    "cna": {
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      "x_legacyV4Record": {
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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.