Cloud Security Alliance Offers Playbook for Red Teaming Agentic AI Systems
- By John K. Waters
- 06/13/25
The Cloud Security Alliance (CSA) has introduced a guide for red teaming Agentic AI systems, targeting the security and testing challenges posed by increasingly autonomous artificial intelligence.
The Red Teaming Testing Guide for Agentic AI Systems outlines practical, scenario-based testing methods designed for security professionals, researchers, and AI engineers.
Agentic AI, unlike traditional generative models, can independently plan, reason, and execute actions in real-world or virtual environments. These capabilities make red teaming — the simulation of adversarial threats — a critical component in ensuring system safety and resilience.
Shift from Generative to Agentic AI
The report highlights how Agentic AI introduces new attack surfaces, including orchestration logic, memory manipulation, and autonomous decision loops. It builds on previous work such as CSA's MAESTRO framework and OWASP's AI Exchange, expanding them into operational red team scenarios.
Twelve Agentic Threat Categories
The guide outlines 12 high-risk threat categories, including:
- Authorization & control hijacking: exploiting gaps between permissioning layers and autonomous agents.
- Checker-out-of-the-loop: bypassing safety checkers or human oversight during sensitive actions.
- Goal manipulation: using adversarial input to redirect agent behavior.
- Knowledge base poisoning: corrupting long-term memory or shared knowledge spaces.
- Multi-agent exploitation: spoofing, collusion, or orchestration-level attacks.
- Untraceability: masking the source of agent actions to avoid audit trails or accountability.
Each threat area includes defined test setups, red team goals, metrics for evaluation, and suggested mitigation strategies.
Tools and Next Steps
Red teamers are encouraged to use or extend agent-specific security tools such as MAESTRO, Promptfoo's LLM Security DB, and SplxAI's Agentic Radar. The guide also references experimental tools such as Salesforce's FuzzAI and Microsoft Foundry's red teaming agents.
"This guide isn't theoretical," said CSA researchers. "We focused on practical red teaming techniques that apply to real-world agent deployments in finance, healthcare, and industrial automation."
Continuous Testing as Security Baseline
Unlike static threat modeling, the CSA's guidance emphasizes continuous validation through simulation-based testing, scenario walkthroughs, and portfolio-wide assessments. It urges enterprises to treat red teaming as part of the development lifecycle for AI systems that operate independently or in critical environments.
The full guide can be found on the Cloud Security Alliance site here.
About the Author
John K. Waters is the editor in chief of a number of Converge360.com sites, with a focus on high-end development, AI and future tech. He's been writing about cutting-edge technologies and culture of Silicon Valley for more than two decades, and he's written more than a dozen books. He also co-scripted the documentary film Silicon Valley: A 100 Year Renaissance, which aired on PBS. He can be reached at [email protected].