Benchmark prompt-injection attacks defenses and recovery pipelines before trusting an LLM app with Open Prompt Injection
Run structured prompt-injection attack and defense experiments against an LLM-integrated app before production by measuring attack success and testing detection or recovery pipelines.
npx skills add agentskillexchange/skills --skill benchmark-prompt-injection-attacks-defenses-and-recovery-pipelines-before-trusting-an-llm-app-with-open-prompt-injection
Use Open Prompt Injection when the job is to benchmark prompt-injection attacks, defenses, and recovery flows against an LLM-integrated application before deployment, not when a user simply wants a generic security library. The workflow is bounded: configure the target task and model, run attack scenarios, measure outcomes such as attack success, and compare detector or localization defenses before trusting the app. That scope boundary, prompt-injection benchmarking and defense evaluation for LLM applications, is narrow enough to function as a publishable skill instead of a plain research toolkit card.