CVE-2007-0081 (GCVE-0-2007-0081)

Vulnerability from cvelistv5 – Published: 2007-01-05 11:00 – Updated: 2024-08-07 12:03
VLAI
Summary
Sunbelt Kerio Personal Firewall (SKPF) 4.3.268 and 4.3.246, and possibly other versions allows local users to provide a Trojan horse iphlpapi.dll to SKPF by placing it in the installation directory.
Severity
No CVSS data available.
CWE
  • n/a
Assigner
References
URL Tags
http://www.matousec.com/info/advisories/Kerio-Fak… x_refsource_MISC
http://www.osvdb.org/33356 vdb-entryx_refsource_OSVDB
http://www.securityfocus.com/archive/1/455624/100… mailing-listx_refsource_BUGTRAQ
http://www.securityfocus.com/bid/21828 vdb-entryx_refsource_BID
http://securityreason.com/securityalert/2095 third-party-advisoryx_refsource_SREASON
https://exchange.xforce.ibmcloud.com/vulnerabilit… vdb-entryx_refsource_XF
Date Public
2007-01-01 00:00
Show details on NVD website
To clipboard 

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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.