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PromptShield — LLM Prompt Security Gateway
PromptShield is a real-time security gateway for LLM-powered applications that detects and blocks malicious prompts before they reach the AI model. It protects against common LLM-specific threats such as prompt injection, jailbreaks, system prompt extraction, data exfiltration, and obfuscation. Every prompt passes through a rule-based, regex-driven detection engine that checks five threat categories and assigns a risk score from 0–100. Based on the score, PromptShield either Allows the prompt (0–29), Sanitizes suspicious phrases (30–59), or Blocks it (60–100). High-risk prompts are stopped before the LLM is called, ensuring a block-before-LLM security layer. Approved prompts are forwarded to the Groq API using the llama-3.1-8b-instant model. The system includes a FastAPI REST backend with Swagger documentation and a Gradio dashboard for live verdicts, request logs, and attack statistics. The backend is deployed on Vercel and the dashboard on Replit, making the project fully live and testable. We chose a rule-based approach for our hackathon MVP because it is fast, lightweight, free, and fully explainable without requiring a second AI model. Current limitations include the absence of semantic/ML detection, persistent storage, authentication, and rate limiting, with these planned as future improvements along with multilingual detection and automated red-team evaluation. PromptShield demonstrates how a lightweight and transparent security gateway can provide meaningful protection against common prompt-based attacks in real time. Built for the AI Infra Summit Hackathon by Sana Arshad (BS Cyber Security, UET Lahore) and Minahel Javed (BS Artificial Intelligence, UET Lahore).
16 Sep 2026
