CVE-2012-0779_OBJECT_TYPE_CONFUSION
Publish date: October 31, 2012
CVE Identifier: CVE-2012-0779
Advisory Date: OCT 31, 2012
DESCRIPTION
This is the Trend Micro detection for exploits taking advantage of the Adobe Flash Player Object Confusion Vulnerability (CVE-2012-0779). This vulnerability could cause the application to crash and potentially allow an attacker to take control of the affected system.
TREND MICRO PROTECTION INFORMATION
Users of Trend Micro Internet Security and Network VirusWall can detect this exploit at the network layer with Network Virus Pattern (NVP) 10315 or later.
Download the latest NVW pattern file from the following Trend Micro webpage:
AFFECTED SOFTWARE AND VERSION
- Adobe Flash Player 11.2.202.233 and earlier versions for Windows
- Macintosh and Linux operating systems
- Adobe Flash Player 11.1.115.7 and earlier versions for Android 4.x
- Adobe Flash Player 11.1.111.8 and earlier versions for Android 3.x and 2.x
Featured Stories
- Beware of MCP Hardcoded Credentials: A Perfect Target for Threat ActorsPoor secret management in MCP servers can lead to serious consequences, including data breaches and supply chain attacks. This article examines the reality of these unsecure configurations and offers practical recommendations that minimize the chances of exposure.Read more
- Lessons in Resilience from the Race to Patch SharePoint VulnerabilitiesIn this article, Trend Micro discusses how the fast-moving attacks using CVE-2025-53770 and CVE-2025-53771 have underscored the essential role of virtual patching and reliable intelligence in protecting organizations against evolving threats.Read more
- Unveiling AI Agent Vulnerabilities Part V: Securing LLM ServicesTo conclude our series on agentic AI, this article examines emerging vulnerabilities that threaten AI agents, focusing on providing proactive security recommendations on areas such as code execution, data exfiltration, and database access.Read more
- Unveiling AI Agent Vulnerabilities Part IV: Database Access VulnerabilitiesHow can attackers exploit weaknesses in database-enabled AI agents? This research explores how SQL generation vulnerabilities, stored prompt injection, and vector store poisoning can be weaponized by attackers for fraudulent activities.Read more