News

Cloud Security Alliance Unveils Red Teaming Playbook for Agentic AI Systems

• By John K. Waters
• 06/03/2025

The Cloud Security Alliance (CSA) has released a comprehensive red teaming guide for 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.

For background on recent enterprise AI security concerns, see related reporting on Pure AI and the emergence of Agentic AI in production systems.