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prompt-injection-detector

DevOps & Security
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Prompt injection detection and prevention for secure LLM applications

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How to use this skill

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  1. Open your project in Codex.
  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
Prompt to paste
I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/ai-agents-conversational/skills/prompt-injection-detector/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/prompt-injection-detector/. Do not write files or run scripts until I approve.

After I approve, install the complete skill folder, including required referenced files, into that project location. Verify it is discoverable, then tell me its actual invocation name and how to use it. Do not claim it is installed until you have verified it.

Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Prompt Injection Detector Skill

Capabilities

  • Detect prompt injection attempts
  • Implement input sanitization
  • Configure detection classifiers
  • Design defense layers
  • Implement canary token detection
  • Create injection logging and alerting

Target Processes

  • prompt-injection-defense
  • tool-safety-validation

Implementation Details

Detection Methods

  1. Pattern Matching: Known injection patterns
  2. ML Classifiers: Trained injection detectors
  3. Canary Tokens: Detect instruction override
  4. LLM-Based: Use LLM to detect manipulation
  5. Perplexity Analysis: Unusual input patterns

Defense Strategies

  • Input preprocessing
  • Prompt structure design
  • Output validation
  • Sandboxed execution
  • Multi-layer defense

Configuration Options

  • Detection threshold
  • Pattern rules
  • Classifier model
  • Action policies
  • Alerting settings

Best Practices

  • Defense in depth
  • Regular pattern updates
  • Monitor false positives
  • Test with red-team inputs

Dependencies

  • rebuff (optional)
  • transformers
  • Custom classifiers