SecureAI_Agent

💡 Inspiration With the rapid growth of AI systems, deepfake audio, manipulated images, and prompt injection attacks are becoming serious threats. We realized that while AI systems are becoming smarter, they are not necessarily becoming safer. This inspired us to build SecureAI Agent, an AI Firewall that protects AI systems before malicious inputs can cause damage. Our goal was to create a security layer that ensures trust and safety in AI-powered applications. 🛡 What it does SecureAI Agent is a multimodal AI security system that analyzes uploaded audio and image files to detect potential threats. It calculates a risk score and classifies the input as: Safe Flagged Blocked The system acts as a protective layer between users and AI systems, preventing malicious content from being processed further. ⚙ How we built it We built SecureAI Agent using: Frontend: Streamlit Backend: FastAPI Programming Language: Python Data Handling: Pandas Visualization: Plotly Workflow: User uploads an audio or image file Backend processes the file using detection modules Individual risk scores are generated A fusion-based scoring system calculates the final risk The result is displayed and logged in scan history The architecture connects frontend → backend → detection modules → risk scoring → final classification. ⚠ Challenges we ran into Designing a reliable risk scoring mechanism Combining multiple detection outputs into one final decision Maintaining real-time performance on CPU Debugging integration issues between frontend and backend Managing time effectively during development 🏆 Accomplishments that we're proud of Built a working prototype within hackathon constraints Successfully implemented multimodal detection (audio + image) Designed a clean, user-friendly dashboard Created a modular and scalable architecture Delivered a functional demo with proper documentation 📚 What we learned Practical implementation of AI security concepts Backend–frontend integration in real-world systems Importance of modular design Efficient debugging and optimization under time pressure How AI security will shape the future of intelligent systems 🚀 What's next for SecureAI_Agent Integrating deep learning-based detection models Adding prompt injection detection for text inputs Deploying on cloud platforms Enabling real-time streaming threat detection Building enterprise-level AI security APIs