LLM Guard Review 2026
Security toolkit for LLMs to detect prompt injection and PII
⭐ 3k+ stars
📜 Open Source
🏷️ skill
Overview
Security toolkit for LLMs to detect prompt injection and PII
Pros
- ✓ Detects prompt injection attacks and jailbreak attempts before they reach your LLM
- ✓ Identifies and redacts PII like emails, phone numbers, and credit card data automatically
- ✓ Runs entirely locally without sending sensitive data to external security services
- ✓ Provides fine-grained control over sanitization rules and detection thresholds
Cons
- ✗ Requires Python expertise and dependency management; more complex setup than plug-and-play solutions
- ✗ Detection accuracy depends on regex patterns and ML models; may have false positives on benign inputs
Key Features
- 🛡️Prompt Injection Detection: Identifies and blocks prompt injection attacks and jailbreak attempts before they reach your LLM, protecting against instruction override exploits.
- 🔍Automatic PII Redaction: Detects and masks sensitive data including emails, phone numbers, credit cards, and SSNs in real-time without manual configuration.
- 🔒Local-Only Processing: Runs entirely on-premises without transmitting sensitive user data to external services, maintaining complete data privacy and compliance.
- ⚡Pre and Post-Request Scanning: Guards both user inputs before processing and LLM outputs after generation, creating dual-layer protection against security risks.
- 📋Configurable Security Policies: Define custom detection rules and thresholds for your specific use case, from strict security to lenient policies based on application needs.
Verdict
LLM Guard is a solid skill solution with 3k+ GitHub stars. It provides focused functionality worth testing against your specific workflow requirements.
Frequently Asked Questions
What is LLM Guard?
LLM Guard is an AI tool in the skill space with 3k+ GitHub stars. Security toolkit for LLMs to detect prompt injection and PII.
Is LLM Guard free?
LLM Guard is licensed under Open Source. Check official website for current details.