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Our research investigates security, fraud, and bot detection through the lens of deep dive analysis and data science.

Fingerprint harvesting in the bot ecosystem

Fingerprint harvesting in the bot ecosystem

bot management · fingerprinting

2026
Published
Last revised

Fingerprint harvesting in the bot ecosystem

Antoine Vastel
bot management fingerprinting

This report uncovers how bot ecosystems harvest and reuse real browser fingerprints, including signals from commercial anti-bot systems, to scale realistic impersonation. These fingerprints are becoming operational assets, enabling more efficient and harder-to-detect automation. The implication is clear: detection systems must assume replay and treat client-side signals as untrusted.

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Fingerprint harvesting in the bot ecosystem

Fingerprint harvesting in the bot ecosystem

bot management · fingerprinting

2026

BotmasterLabs: Powering an Era of Spam

BotmasterLabs: Powering an Era of Spam

bot management · fingerprinting · spam

2026

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Meet the team behind Castle's security research

Antoine Vastel

Antoine Vastel

Browser fingerprinting, bot detection, web security
Kurt Nistelberger

Kurt Nistelberger

Mobile security, reverse engineering, device signals
Naif Mehanna

Naif Mehanna

Detection engineering, email intelligence, Hardware fingerprinting
Nicolas Sama

Nicolas Sama

Obfuscation, codec architecture, anti-tampering
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Device Fingerprinting Engineer

Fingerprinting, ML

Build fingerprinting systems that survive spoofing, drift, and browser evolution. Focus on signals and matching logic that stay reliable under real-world conditions.

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Detection Automation Engineer, Bot & Fraud Detection

Bot detection, fingerprinting, ML

Build detection systems that actually survive contact with attackers. Prioritize clarity, robustness, and long-term resilience over rule sprawl and complexity.

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Mobile Engineer

Mobile SDKs, iOS/Android, performance, reliability

Build mobile SDKs that run reliably inside millions of devices. Focus on performance, stability, and resilience in adversarial environments.

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