Resources
Technical deep-dives, security research, and engineering guides from the Lightning Research team.
How we built an attention-based neural model for device fingerprint matching — including signal drift detection, stability benchmarking, and DeepFPD-style script classification.
An in-depth look at the research behind cross-browser device fingerprinting and how GPU-level signals enable identification across browsers.
Learn how combining device fingerprints with behavioral analysis can detect automated credential stuffing attacks in real-time.
A practical guide to implementing device fingerprinting while maintaining GDPR compliance and user privacy expectations.
Why WebGL rendering tasks produce more stable and unique device signatures than traditional canvas-based fingerprinting approaches.
An overview of modern bot detection techniques, from behavioral biometrics to hardware fingerprinting, and where the industry is heading.
Full engine SDK with 90+ signals, behavioral biometrics, lies detection, headless checks, and built-in consent management. Zero dependencies, TypeScript-first.