CVE-2010-4142 (GCVE-0-2010-4142)

Vulnerability from cvelistv5 – Published: 2010-11-01 18:00 – Updated: 2024-09-16 22:08
VLAI
Summary
Multiple stack-based buffer overflows in DATAC RealWin 2.0 Build 6.1.8.10 and earlier allow remote attackers to cause a denial of service (crash) and possibly execute arbitrary code via a long (1) SCPC_INITIALIZE, (2) SCPC_INITIALIZE_RF, or (3) SCPC_TXTEVENT packet. NOTE: it was later reported that 1.06 is also affected by one of these requests.
Severity
No CVSS data available.
CWE
  • n/a
Assigner
References
URL Tags
http://www.exploit-db.com/exploits/15259 exploitx_refsource_EXPLOIT-DB
http://www.securityfocus.com/bid/44150 vdb-entryx_refsource_BID
http://aluigi.org/adv/realwin_1-adv.txt x_refsource_MISC
http://www.exploit-db.com/exploits/15337 exploitx_refsource_EXPLOIT-DB
http://secunia.com/advisories/41849 third-party-advisoryx_refsource_SECUNIA
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

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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.


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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.