AI Red Teaming & Adversarial Testing
AgentClad Security executes targeted adversarial red team operations designed specifically for production agentic applications and LLM systems. Standard pentesting fails to uncover model manipulation, system-prompt extraction, or multi-step agent tool abuse. Our operations simulate real-world adversaries deploying direct prompt injection, indirect prompt injection via context data, tool argument poisoning, and memory corruption payloads.
Technical Scoping Activities
- Direct and indirect prompt injection payload generation and automated fuzzing
- System prompt extraction, guardrail bypass, and jailbreak resilience testing
- Agentic tool-call hijacking and parameter poisoning evaluation
- Multi-turn conversation state corruption and memory buffer manipulation
- RAG context poisoning and exfiltration path verification
Concrete Eng Deliverables
- Adversarial Red Team Assessment ReportArtifact Label: [Sample Audit Artifact] - Executive summary and detailed technical findings with proof-of-concept exploits and impact scoring.
- Jailbreak & Injection Vulnerability MatrixArtifact Label: [Sample Audit Artifact] - Comprehensive matrix categorizing tested attack vectors, bypass rates, and model failure modes.
- System Prompt & Guardrail Hardening RecommendationsArtifact Label: [Sample Audit Artifact] - Concrete engineering fixes, system prompt refactorings, and input/output filter rules.
Engagement RACI & Prerequisites
- Design and execute tailored adversarial attack suites based on threat models.
- Document all successful exploit vectors with reproducible steps.
- Deliver engineering-ready remediation guidelines and guardrail rules.
- Conduct a post-remediation re-test to verify fix efficacy.
Explicit Engagement Exclusions
- Physical facility security testing or general corporate phishing.
- Distributed denial of service (DDoS) infrastructure attacks.
- Modification or corruption of live production database records.
Practice Area FAQs
Will red teaming impact our production service availability?
All red team tests are conducted against isolated staging or sandbox environments with controlled API keys to prevent production downtime or data corruption.
How do you handle non-deterministic outputs from LLMs during testing?
We execute multi-pass automated fuzzing runs with temperature controls and statistical verification to ensure finding reproducibility across probabilistic responses.
Schedule a Technical Scoping Session for AI Red Teaming & Adversarial Testing
Discuss your system architecture, deployment timeline, and compliance targets directly with our AI security engineers.