How-To
How to Prevent Prompt Injection
Practical defense techniques for protecting LLM applications from manipulation.
· 8 min read
Prompt injection is the #1 security risk for LLM applications. Attackers craft inputs that override your system instructions, potentially exfiltrating data or causing harmful outputs.
Defense Layer 1: Input Validation
- Length limits: Restrict input size to prevent context overflow
- Character filtering: Remove or escape special characters
- Pattern detection: Flag inputs containing instruction-like patterns
- Rate limiting: Prevent rapid probing attempts
Defense Layer 2: Prompt Architecture
- Clear delimiters: Separate system instructions from user input
- Instruction reinforcement: Repeat critical instructions after user input
- Role separation: Use system messages for instructions, not user messages
Defense Layer 3: Output Filtering
- Content classification: Detect harmful or unexpected outputs
- Guardrails: Block responses that violate policies
- Sanitization: Remove sensitive data before returning
Defense Layer 4: Detection & Monitoring
- Real-time detection: Flag injection attempts as they occur
- Anomaly detection: Identify unusual input patterns
- Audit logging: Record all interactions for review
- Alerting: Notify security team of attacks
DriftRail Prompt Injection Detection
DriftRail's Growth tier includes automated prompt injection detection:
- Classifies inputs for injection patterns
- Flags manipulation attempts in real-time
- Integrates with guardrails to block attacks
- Provides audit trail for security review
FAQ
Can prompt injection be fully prevented?
No single technique is foolproof. Defense in depth with multiple layers significantly reduces risk but can't eliminate it entirely. Continuous monitoring is essential.
What about indirect prompt injection?
Indirect injection through retrieved content (RAG) is harder to prevent. Sanitize retrieved documents and treat all external content as untrusted.
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