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ClaudeCodexOpenClawData & Analytics
Dave AI
Prompt Injection Detector Skill
Prompt injection detection and prevention for secure LLM applications
instructions.md
--- name: prompt-injection-detector-f3ff6727f363 description: Prompt injection detection and prevention for secure LLM applications allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:hallucination-mitigation-fact-checking, skill-area:safety-redteaming] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:feature-development, workflow:ml-model-lifecycle] --- # 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--- name: prompt-injection-detector-f3ff6727f363 description: Prompt injection detection and prevention for secure LLM applications allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:hallucination-mitigation-fact-checking, skill-area:safety-redteaming] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:feature-development, workflow:ml-model-lifecycle] --- # 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
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Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.