Agent 10 · AI Security · Adversarial Testing
Adversarially tests LLM systems for prompt injection vulnerabilities, identifies attack vectors, evaluates guardrail robustness, and suggests mitigations.
Tests direct injection, indirect injection via external content, role-play jailbreaks, delimiter confusion, context window manipulation, and system prompt exfiltration.
Evaluates input filters, output filters, instruction hierarchy enforcement, refusal robustness, and whether safety layers can be bypassed through multi-turn manipulation.
Suggests concrete fixes: prompt hardening, input sanitisation, privilege separation, monitoring hooks, and evaluation frameworks to measure guardrail effectiveness over time.