Real-Time Transaction Anomaly Engine

Continuously scans every transaction across supported EVM chains (Ethereum, Polygon, Arbitrum) for suspicious patterns like flash loan attacks, price oracle manipulation, and smart contract exploits.

Analyzes wallet interaction history, transaction frequency, and counterparty reputation to identify anomalous behavior that static rules miss, such as newly funded wallets executing complex DeFi attacks.

Self-improving ML models trained on billions of historical transactions automatically adapt to new attack vectors, reducing false positives and catching sophisticated, novel threats.

Assigns a dynamic risk score (0-100) to every transaction and wallet. Triggers instant, configurable alerts via Slack, Discord, or webhooks for high-risk events, enabling rapid response.

Proactively scans for known vulnerability patterns (reentrancy, integer overflow) in your deployed contracts and flags interactions that attempt to exploit them, acting as a runtime security layer.

Detect and block malicious transactions (flash loan attacks, MEV exploits, wash trading) in real-time before they impact your protocol. Reduces incident response time from hours to milliseconds.

Provide users with transparent, real-time security validation for every transaction. This demonstrable safety layer increases user confidence and reduces churn from security incidents.

Automated, auditable logs of all anomaly detection events and risk assessments. Streamlines compliance with emerging DeFi regulations (e.g., Travel Rule, AML) and security audits.

Minimize financial losses from exploits and fraud. Demonstrating proactive risk management can significantly lower protocol insurance premiums and operational overhead.

Integrate real-time security alerts and health dashboards directly into your UI. Turn security from a hidden cost into a visible, marketable feature that attracts sophisticated users and institutions.

Deploy new smart contract functions or financial products with an embedded security monitor. Accelerate development cycles by catching logic flaws and economic vulnerabilities during testing and live rollout.