AI Agent Prompt Injection & Security Risk Scanner
Paste your system prompt, choose your exposure profile, and check the security controls you already have in place. Get a risk score, top attack paths, and a prioritized fix list.
1. Agent exposure
No external users, no sensitive data.
The scanner looks for missing delimiters, instruction-override phrases, secret disclosure, and roleplay hooks.
2. Security controls
Check each control your agent already implements. Missing high-weight controls raise risk and appear in the fix list.
Overall risk score
0
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Open critical controls
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Controls implemented
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Top risk category
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Est. mitigation cost
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Risk breakdown by category
Prioritized fix list
Frequently asked questions
What is prompt injection?
Prompt injection is an attack where user input overrides or leaks the system prompt, hidden instructions, or tool policies. It can happen directly in chat input or indirectly through retrieved documents, emails, web pages, or tool outputs.
Can a scanner replace a security audit?
No. This scanner is a self-service screen that scores common control gaps and prompt signals. For production systems, pair it with manual red-teaming, code review, and a full security audit.
Why do tools increase risk so much?
Tools let the agent take real-world actions. If an attacker can manipulate tool arguments or chain unintended calls, the blast radius is much larger than a text-only chatbot.
What is indirect prompt injection?
Indirect injection hides malicious instructions in data the agent retrieves, such as a web page, PDF, email, or database row. The model then follows those instructions because it cannot distinguish trusted system text from untrusted content.
Which fix usually has the highest impact?
Separating trusted instructions from untrusted content with delimiters, validating every tool call against a strict schema, and running an output guard layer after the LLM are the highest-impact fixes for most agents.