Anti-Fraud & Sybil Attack Prevention Systems

Proprietary behavioral analysis and on-chain pattern recognition identify and block bot farms and Sybil clusters before they can manipulate your marketplace or token launch. Integrates directly with your smart contracts and frontend.

Continuous monitoring and automated transaction interception for known exploit patterns (e.g., reentrancy, flash loan attacks) targeting your marketplace's core logic. Acts as a firewall for your deployed contracts.

Assign dynamic risk scores to every interacting wallet based on transaction history, asset provenance, and network behavior. Enforce tiered access or require additional verification for high-risk actors.

Prevent Sybil attackers from draining token distributions and reward pools. Our system validates user eligibility and authentic engagement, ensuring incentives reach real players and community members.

Maintain a permanent, auditable ledger of all flagged activities and enforcement actions. Generate compliance reports for sanctioned wallet interactions and suspicious transaction patterns.

Tailor detection logic to your game's specific mechanics and economic model. Our API allows your team to define custom rules, manage allow/deny lists, and query threat intelligence in real-time.

We conduct a deep-dive analysis of your platform's specific attack vectors and user flows. This includes on-chain transaction pattern review and off-chain behavioral analysis to design a tailored defense architecture.

Seamless integration of our detection engine via API or SDK. We handle the deployment of real-time monitoring agents and on-chain validator nodes to ensure zero disruption to your live service.

We configure and fine-tune detection rules for Sybil clusters, wash trading, and flash loan attacks based on your tokenomics. Includes whitelist/blacklist management and threshold optimization.

Ongoing surveillance with automated alerts for suspicious activity. You receive detailed dashboards and weekly reports on blocked attacks, wallet clustering, and network health metrics.