Overview
This workflow automates the detection of suspicious login attempts by analyzing user, device, and IP address data in real time. It leverages multiple decision nodes and integrations to assess login events for potential threats.
Key Features
- Webhook Trigger: Captures new /login events instantly.
- Data Extraction: Gathers relevant login details, including user agent and IP address.
- Historical Analysis: Queries a Postgres database for the user's last 10 logins to identify anomalies.
- IP Intelligence: Integrates with external IP APIs to assess geolocation and risk factors.
- Device & Browser Parsing: Analyzes user agent strings to detect new or unusual devices/browsers.
- Conditional Logic: Multiple 'if' nodes evaluate threat levels and merge results for comprehensive analysis.
Benefits
- Enhanced Security: Quickly identifies and flags suspicious login behavior, reducing risk of unauthorized access.
- Automation Efficiency: Eliminates manual review, saving significant time for security teams.
- Scalable Analysis: Handles high login volumes with consistent, automated checks.
Use Cases
- Protecting user accounts in SaaS platforms.
- Monitoring employee logins for unusual activity.
- Integrating with incident response systems for automated alerts.
Integrations
- Postgres database for historical login data.
- External IP intelligence APIs.
- Webhook for real-time event capture.
