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CVE-2009-0769 (GCVE-0-2009-0769)

Vulnerability from cvelistv5 – Published: 2009-03-03 18:00 – Updated: 2024-08-07 04:48
VLAI
Summary
QIP 2005 build 8082 allows remote attackers to cause a denial of service (CPU consumption and application hang) via a crafted Rich Text Format (RTF) ICQ message, as demonstrated by an {\rtf\pict\&&} message. NOTE: the vulnerability may be in Sergey Tkachenko TRichView. If so, then this should not be treated as a vulnerability in QIP.
Severity
No CVSS data available.
CWE
  • n/a
References
URL Tags
http://www.securityfocus.com/bid/33609 vdb-entryx_refsource_BID
http://www.osvdb.org/51755 vdb-entryx_refsource_OSVDB
http://www.securityfocus.com/archive/1/500656/100… mailing-listx_refsource_BUGTRAQ
http://secunia.com/advisories/33851 third-party-advisoryx_refsource_SECUNIA
Date Public
2009-02-05 00:00
Show details on NVD website

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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.

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Detection rules are retrieved from Rulezet.

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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.


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