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VAR-201309-0151

Vulnerability from variot - Updated: 2025-04-11 23:08

Multiple stack-based buffer overflows in Adobe Reader and Acrobat before 10.1.8 and 11.x before 11.0.04 on Windows and Mac OS X allow attackers to execute arbitrary code via unspecified vectors. Adobe Acrobat and Reader are prone to multiple stack-based buffer-overflow vulnerabilities. Attackers can exploit these issue to execute arbitrary code in the context of the user running the affected applications. Failed exploit attempts will likely cause denial-of-service conditions. Note: These issues were previously discussed in BID 62293 (Adobe Acrobat and Reader APSB13-22 Multiple Remote Code Execution Vulnerabilities), but have been moved to their own record for better documentation. Adobe Reader is a free PDF file reader, and Acrobat is a PDF file editing and conversion tool

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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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