ThreatDefender

Inspiration

Cybersecurity threats are becoming increasingly common, and many users struggle to identify malicious files and URLs before damage occurs. We built ThreatDefender to provide an AI-powered security assistant that helps users quickly analyze potential threats.

What it does

ThreatDefender analyzes uploaded files and URLs, detects suspicious content, provides AI-generated threat assessments, and stores scan results for future reference.

How we built it

We built ThreatDefender using Spring Boot, Java, Gemini AI, MongoDB, and MCP integration. The system processes files and URLs, performs AI-based threat analysis, and generates actionable security insights.

Challenges we ran into

Integrating AI-driven threat analysis, handling different file types, and designing a workflow that provides meaningful security recommendations.

Accomplishments that we're proud of

Successfully building an intelligent cybersecurity agent that combines AI analysis, threat detection, and data management into a single platform.

What we learned

We gained experience in AI integration, cybersecurity workflows, MCP architecture, and scalable backend development.

What's next for ThreatDefender

Future improvements include advanced malware detection, real-time monitoring, automated response actions, and expanded MCP integrations.

Built With

• css
• gemini-ai
• html
• java
• javascript
• mcp
• mongodb
• spring-boot