As artificial intelligence evolves from simple chatbots to sophisticated autonomous systems, a new security challenge emerges. A comprehensive report from ISACA’s Special Interest Group reveals why traditional cybersecurity measures fall short when protecting “agentic AI”—systems where multiple AI agents work together, make independent decisions, and coordinate complex tasks without constant human oversight.
Why Agentic AI Changes Everything
Unlike conventional AI that follows predetermined scripts, agentic systems can perceive situations, plan actions, delegate tasks, and learn from outcomes. Think of them as digital employees that collaborate—autonomously managing customer service, orchestrating supply chains, or even handling financial transactions. While this autonomy promises remarkable efficiency gains, it also creates unprecedented security vulnerabilities.
The report, titled “Best Practices for Secure Adoption and Use of Agentic AI,” identifies a critical problem. When AI agents communicate and share information across networks, a single compromised agent can rapidly poison an entire system. Traditional firewalls and access controls weren’t designed for this dynamic, distributed intelligence.
The Five Major Threats
Security professionals now face five distinct threat categories. Input compromise occurs when malicious data enters the system, distorting how agents reason and make decisions. Agent compromise involves corrupting an agent’s goals or code, turning it into a malicious insider. Multi-agent exploitation targets the shared infrastructure where agents operate, while communication manipulation attacks the channels through which agents coordinate. Finally, identity abuse exploits weak credential management to impersonate legitimate agents.
Real-world incidents illustrate these risks dramatically. Researchers have demonstrated prompt injection techniques that bypass security guardrails, while one prankster manipulated a dealership chatbot into offering a $76,000 vehicle for just $1. More seriously, AI coding tools have accidentally wiped production databases, and compromised AI influencers have resulted in cryptocurrency thefts exceeding $100,000.
Four Principles for Secure Deployment
The framework recommends four foundational principles. Observability ensures every agent action is captured and reviewable in real time. Bounded autonomy restricts agents to operating within clearly defined, revocable limits. Ephemeral identity means credentials expire automatically after single-use sessions, preventing unauthorized access. Finally, preserving coordination trust ensures agent communications remain authentic and tamper-proof.
A Roadmap to Maturity
Organizations can assess their readiness using a five-level maturity model that progresses from unmanaged experimentation to fully verified coordination. Most companies currently operate at Level 1 or 2, with minimal oversight and significant vulnerabilities. Reaching Level 3 requires implementing basic governance—agent registration, role definitions, and escalation pathways for high-stakes decisions.
Practical Next Steps
Security leaders should immediately inventory all agentic AI deployments, establish clear ownership across teams, and deploy observability systems to track agent behavior. The report emphasizes that security cannot be an afterthought bolted onto existing systems; it must be embedded into how agents plan, communicate, and execute tasks from the ground up.
As enterprises rush to deploy agentic AI in critical workflows, the stakes couldn’t be higher. Organizations that proactively implement these security frameworks will capture AI’s transformative benefits while avoiding catastrophic breaches. Those that don’t may find themselves managing cascading failures at machine speed—a scenario no human security team can effectively contain.
