ThreatFusion AI

Inspiration

Security teams are drowning in alert fatigue. With tools like CrowdStrike, Cloudflare, Okta, Defender, and AWS CloudTrail all generating alerts separately, analysts lose visibility. Multi-stage attacks look unrelated, slowing response and increasing risk. We wanted to build a system that shows the full attack story in one place.

What it does

ThreatFusion AI unifies alerts from all security tools into a single dashboard. It uses AI to correlate related events, detect multi-stage attacks, visualize the kill chain, and highlight impacted assets. Teams get context, priority, and recommended response actions instantly.

How we built it

We used Base44 for AI logic, alert correlation, and backend processing. The frontend is built with HTML, CSS, JavaScript, and Base44 UI components. Alerts are normalized into a common structure, passed into an AI correlation engine, and visualized with a clean JS dashboard showing timelines and relationships.

Challenges we ran into

Normalizing alerts from different security platforms

Creating accurate AI correlations without false links

Designing a timeline UI that is clear but not overwhelming

Handling high alert volume efficiently

Accomplishments that we're proud of

Built a unified threat dashboard

AI successfully identifies multi-stage attack chains

Clear visualization of attack timelines and affected assets

Smooth Base44 + JS interface that SOC analysts can use

What we learned

We learned how complex and noisy real security alerts can be, how difficult correlation is, and how much a clear UI improves analyst speed. We also discovered the value of AI in reducing noise and highlighting true threats.

What's next for ThreatFusion AI

Live integrations with SIEMs like Splunk, QRadar, Chronicle

Automated incident-response playbooks

Predictive attack-path modeling

Real-time user and entity behavior analytics

Enterprise-grade RBAC and multi-tenant deployments