Apache OFBiz Multiple Cross Site Scripting and HTML Injection Vulnerabilities
Severity: MEDIUM
CVE Identifier: CVE-2010-0432
Advisory Date: JUL 21, 2015
DESCRIPTION
Apache OFBiz (Open For Business) is prone to multiple cross-site-scripting and HTML-injection vulnerabilities because it fails to properly sanitize user-supplied input before using it in dynamically generated content.
Attacker-supplied HTML and script code would run in the context of the affected browser, potentially allowing the attacker to steal cookie-based authentication credentials or to control how the site is rendered to the user. Other attacks are also possible.
TREND MICRO PROTECTION INFORMATION
Apply associated Trend Micro DPI Rules.
SOLUTION
Trend Micro Deep Security DPI Rule Number: 1000552
Trend Micro Deep Security DPI Rule Name: 1000552 - Generic Cross Site Scripting(XSS) Prevention
AFFECTED SOFTWARE AND VERSION
- apache open_for_business_project 09.04
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