• Accurately identifying security vulnerabilities across diverse web systems

• Reducing false positives from automated security scans

• Coordinating secure interactions between enterprises and bounty hunters

• Managing sensitive vulnerability data safely

• Scaling scanning and reporting processes across multiple targets

The team developed an AI-powered bug bounty platform that combines automated cyber scanning with human-driven validation.

Key solution components include:

• AI-based cyber scanning system using machine learning to analyze websites and detect potential vulnerabilities

• Bug bounty task marketplace where enterprises publish security testing challenges

• Secure workflow for bounty hunters to submit, track, and validate vulnerability reports

• Performance analysis and training recommendations for security researchers

• Safety mechanisms to control access, disclosure, and responsible reporting

Results:

• Delivered a production-ready AI cybersecurity platform

• Enabled continuous vulnerability discovery through AI and human collaboration

• Improved efficiency of security testing compared to manual-only approaches

• Provided enterprises with structured and scalable bug bounty management

• Established a foundation for long-term expansion in cybersecurity services

Key Features:

• AI-driven vulnerability scanning

• Bug bounty mission matching

• Bid-ask mechanism for security tasks

• Secure vulnerability reporting workflow

• Performance analysis and training insights

• Safety controls for responsible disclosure

Team Composition

• 1 Project Manager

• 3 Developers

• 1 AI Engineer

• 1 DevOps Engineer

• 1 Security Specialist

Tech Stack

• Frontend: Next.js

• Backend: NestJS

• AI / ML: TensorFlow

• Database: PostgreSQL

• Messaging & Queue: SQS

• CI/CD: Automated CI/CD pipeline

• Infrastructure: Kubernetes, KEDA