Why Trust Your Agent? Empirical Security Gains from TRiSM-Guided Agentic Workflows in Healthcare
arXiv:2606.28666v1 Announce Type: cross Abstract: Agent-based AI has enabled the automation of tasks by exposing application tools and resources to large language models (LLMs). However, to improve scope and accuracy, agents are often given access rights that exceed those of ordinary users, introducing significant security risks. AI is routinely integrated into applications with a disregard to security, risking data exposure and breaching regulations. This paper applies the AI Trust, Risk, and Security Management (TRiSM) framework to a medical report-generation application to demonstrate how a
The rapid deployment of agent-based AI in critical applications like healthcare is forcing a confrontation with inherent security vulnerabilities that demand proactive solutions.
This paper directly addresses the critical security and trust issues in agent-based AI, which are paramount for their safe and widespread adoption, especially in sensitive sectors.
The focus on applying structured frameworks like TRiSM to agentic workflows shifts the conversation from purely capability-driven AI development to security-first integration, ensuring safer deployment.
- · AI Trust, Risk, and Security Management (TRiSM) framework developers
- · Cybersecurity firms specializing in AI
- · Healthcare organizations adopting secure AI agents
- · Responsible AI developers
- · Unsecured AI agent platforms
- · Organizations disregarding AI security
- · Developers prioritizing speed over security
- · Patients whose data might be compromised
Increased industry adoption of security-by-design principles for AI agents, particularly in regulated environments.
Development of new compliance and regulatory standards specifically tailored for agent-based AI systems and their extensive access rights.
The emergence of 'AI security audits' as a standard and mandatory component prior to deployment of agentic workflows in enterprise applications.
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Read at arXiv cs.AI