CSA: Agentic AI: Understanding Its Evolution, Risks, and Security Challenges

May 12, 2025

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Source URL: https://www.troj.ai/blog/agentic-ai-risks-and-security-challenges
Source: CSA
Title: Agentic AI: Understanding Its Evolution, Risks, and Security Challenges

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**Summary:** The text discusses the evolution and significance of agentic AI systems, highlighting the complexities and security challenges that arise from their autonomous and adaptive nature. It emphasizes the need for robust governance, proactive security measures, and the implementation of frameworks to address the unique risks associated with these systems, particularly in the context of large language models (LLMs).

**Detailed Description:**
The article delineates the emerging concept of agentic AI, which blends traditional agentic systems with advancements in LLMs and generative AI. The discussion pivots around the implications of these technologies for security and risk management.

– **Definition of Agentic AI:**
– Comprised of multiple interacting agents performing autonomous tasks.
– Enhanced by LLMs to operate with minimal human intervention.

– **Differences from Traditional AI:**
– **Autonomy:** Agentic AI can make decisions independently.
– **Adaptability:** It learns continuously without needing constant updates.
– **Complex Problem Solving:** Executes multi-step tasks proactively.

– **Key Components of Agentic AI:**
– **Large Language Models:** Facilitate understanding and interaction.
– **Integrated Services/Tools:** Enable agent actions.
– **Memory Management:** Provides contextual history for improved decision-making.
– **Communication Interfaces:** Ensure effective human-agent collaboration.

– **Security Implications:**
– Convergence of automation and complexity necessitates new security protocols.
– Distinction between agentic safety (preventing harmful actions) and agentic security (protecting against malicious exploitation).
– Identification of new vulnerabilities, such as excessive agency, memory poisoning, and cascading hallucinations.

– **Importance of Agentic AI Security:**
– As the use of AI expands, agentic AI requires diligent security measures to prevent exploitation and mitigate unintended consequences.
– Regulatory and compliance needs will evolve alongside technological advancements.

– **Recommended Approaches for Security:**
– Development of new governance frameworks (e.g., OWASP and MITRE OCCULT).
– Adoption of a proactive security-first approach in designing and implementing agentic AI systems.
– Continuous monitoring and logging of agent behaviors to preemptively address potential issues.

The text provides crucial insights for security and compliance professionals, underpinning the necessity to adapt existing frameworks while embracing the capabilities of agentic AI. It indicates that as these systems become more integrated into business processes, the potential risks they bring must be thoughtfully managed through innovative security strategies.

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