CVE-2015-8991 (GCVE-0-2015-8991)

Vulnerability from cvelistv5 – Published: 2017-03-14 22:00 – Updated: 2024-08-06 08:36
VLAI
Summary
Malicious file execution vulnerability in Intel Security McAfee Security Scan+ (MSS+) before 3.11.266.3 allows attackers to make the product momentarily vulnerable via executing preexisting specifically crafted malware during installation or uninstallation, but not during normal operation.
Severity
7.0 (High)
CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
CWE
  • Malicious file execution vulnerability
Assigner
intel CNA under the mitre root
CNA scorecard C 60/100 over 96 records in the last 180 days details
References
Impacted products
Vendor Product Version CPE status
Intel McAfee Security Scan+ (MSS+) Affected: before 3.11.266.3
guessed Create a notification for this product.
Date Public
2015-12-02 00:00
Show details on NVD website
To clipboard 

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Taxonomy of the tags.





Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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.



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.