QuickToolPro
aiChecker

Prompt Injection Scanner

Scan prompts, retrieved content, or tool instructions for injection patterns, exfiltration requests, and risky overrides.

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Run check

Checker

Inspect the input and turn gaps into fixes.

Paste the source, review the signals, and copy only the fixes you can verify after publishing or sharing.

Input

Add URL, text, logs, metadata, or policy details.

Signals

Review score, warnings, mismatches, or limits.

Fixes

Copy recommendations and verify the live result.

Scan profile

Paste untrusted content, prompt text, RAG snippets, or tool instructions to scan.

Pattern scanning is a review aid, not a proof of safety.

Privacy: This tool runs entirely in your browser. No data is sent to our servers. We don't store, share, or have access to any of the information you process here.

Input, signals, and fixes

Review summary

Turn prompt planning into a package you can copy into an AI tool, API request, or prompt library.

Budget
Token count, context use, chunk size, or cost estimate.
Prompt package
Structured instructions, constraints, examples, and output format.
Safety note
Injection risk, missing context, or model-routing checks.

Audit examples

How to verify the findings

The Prompt Injection Scanner checks prompts, retrieved web content, knowledge-base snippets, and agent tool instructions for common injection and exfiltration patterns.

It is a deterministic review aid. It does not call a model and does not prove that a prompt is safe, but it helps surface risky language before content reaches an AI workflow.

Common use cases

  • Review RAG passages before they are inserted into a system prompt or tool-using agent.
  • Check public webpage content for instructions that try to override assistant behavior.
  • Create a short mitigation checklist for prompt libraries and AI automation flows.

How to use it well

  1. Paste the prompt, retrieved document, webpage text, or tool instruction you want to inspect.
  2. Choose the source type and scan strictness.
  3. Review high-risk findings, affected snippets, and mitigation notes.
  4. Update your system prompt boundaries, tool permissions, and output validation rules.

Practical tips

  • Separate trusted system instructions from untrusted user or webpage content.
  • Treat requests to reveal hidden prompts, ignore rules, export secrets, or call tools as high-risk signals.
  • Use allowlists and schema validation for tool calls instead of relying on prompt wording alone.

Limitations to know

  • Attack wording changes constantly, so pattern scanning is only one layer of defense.
  • Safe-looking content can still cause problems when combined with weak tool permissions.

Continue with a guide

AI Prompt Planning Guide

Token budget -> context plan -> chunks -> cost -> safety check.

Open guideOpen Prompt Lab
1

Count the prompt

Check whether the prompt leaves room for examples, retrieved context, and output.

AI Token Counter
2

Plan the context window

Reserve space for instructions, user content, tool messages, and final answer.

Context Window Planner
3

Shape retrieval chunks

Split long source material into overlap-aware chunks for RAG or knowledge workflows.

RAG Chunking Tool
4

Check safety and cost

Estimate API cost and scan untrusted text for prompt-injection patterns.

Prompt Injection Scanner

FAQ

Q: Can this prove a prompt is safe?

A: No. It finds common risky patterns and review gaps. You still need model-side controls, tool permissions, and output validation.

Q: Does it send my prompt to an AI model?

A: No. Pattern checks run locally in the browser.

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Privacy: This tool runs entirely in your browser. No data is sent to our servers. We don't store, share, or have access to any of the information you process here.