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PromptShield LLMPrompt Injection Defense
Production grade prompt injection defense middleware for LLM
5 followers
Production grade prompt injection defense middleware for LLM
5 followers
PromptShield sits between your users and your LLM, blocking prompt injection attacks before they reach the model. 4 layers of defense: 1. Input Classifier – detects malicious patterns 2. Context Sanitizer – strips injected instructions 3. Prompt Integrity Checker – validates structure 4. Output Monitor – catches successful injections Tunable aggression, API auth, rate limiting, audit logs, Python SDK, Docker. Benchmark tested. Built by a CS student from Nairobi, Kenya.
The four-layer setup sounds solid, especially the output monitor since most tools skip that. One thing that would make this way more useful for teams: a rule sharing format or community-maintained blocklist for common injection payloads. Right now every company rediscovers the same patterns. A GitHub repo where users PR new attack signatures and you ship them as versioned feeds would save everyone time and make the classifier sharper with real-world data instead of just synthetic benchmarks.