CVE-2011-2735 (GCVE-0-2011-2735)

Vulnerability from cvelistv5 – Published: 2011-08-23 21:00 – Updated: 2024-08-06 23:08
VLAI
Summary
Multiple buffer overflows in EMC AutoStart 5.3.x and 5.4.x before 5.4.1 allow remote attackers to cause a denial of service (daemon crash) or possibly execute arbitrary code by sending a crafted message over TCP.
Severity
No CVSS data available.
CWE
  • n/a
References
URL Tags
http://securityreason.com/securityalert/8352 third-party-advisoryx_refsource_SREASON
http://secunia.com/advisories/45703 third-party-advisoryx_refsource_SECUNIA
http://securitytracker.com/id?1025958 vdb-entryx_refsource_SECTRACK
http://www.securityfocus.com/bid/49238 vdb-entryx_refsource_BID
https://exchange.xforce.ibmcloud.com/vulnerabilit… vdb-entryx_refsource_XF
http://www.securityfocus.com/archive/1/519371/100… mailing-listx_refsource_BUGTRAQ
Date Public
2011-08-18 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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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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