Adobe Reader Doc.printSeps() Memory Corruption Vulnerability
Publish date: July 21, 2015
Severity: CRITICAL
CVE Identifier: CVE-2010-4091
Advisory Date: JUL 21, 2015
DESCRIPTION
The EScript.api plugin in Adobe Reader and Acrobat 10.x before 10.0.1, 9.x before 9.4.1, and 8.x before 8.2.6 on Windows and Mac OS X allows remote attackers to execute arbitrary code or cause a denial of service (application crash) via a crafted PDF document that triggers memory corruption, involving the printSeps function. NOTE: some of these details are obtained from third party information.
TREND MICRO PROTECTION INFORMATION
Apply associated Trend Micro DPI Rules.
SOLUTION
Trend Micro Deep Security DPI Rule Number: 1004506
Trend Micro Deep Security DPI Rule Name: 1004506 - Adobe Reader Doc.printSeps() Memory Corruption Vulnerability
AFFECTED SOFTWARE AND VERSION
- Adobe Acrobat Reader 8.1.7
- Adobe Acrobat Reader 9.2
- Adobe Acrobat Reader 9.4
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