Adversarial testing toolkit built from active engagements against frontier LLMs. Prompt injection pattern detection and structured adversarial test suite - real techniques, sanitized findings.
Regex-based pattern scanner against 9 real adversarial signature classes - the same patterns used to triage prompts during live engagements. Click any example below or write your own, then hit Analyse.
Click an example above or type a prompt, then hit Analyse.
Simulated run of the actual test suite structure used during real engagements - same categories, same test names, realistic timing. Results are randomised on each run, not live model calls. The test case taxonomy and failure modes are real; the per-run scores are illustrative.
Sanitized, NDA-compliant findings from an active red teaming engagement. Model identifiers redacted.
Composite role-play + encoding attacks bypassed content filters with 83% success rate across evaluated models.
Indirect prompt injection via retrieved documents succeeded in tool-augmented deployments in 7/10 test scenarios.
Many-shot jailbreaking demonstrated context-length dependency - models with larger windows showed higher vulnerability.
System prompt extraction via translation-chaining succeeded in 49% of cases; partial disclosure in additional 23%.
All findings are sanitized and NDA-compliant. Model identifiers, client details, and specific exploit strings have been redacted. This framework and its findings are presented for educational and portfolio purposes only. Responsible disclosure procedures were followed throughout the engagement.