How E0G Detects Vulnerabilities Across Blockchain Networks

E0G monitors transactions across seven blockchain networks simultaneously: Ethereum, Arbitrum, Base, Avalanche, Optimism, Polygon, and BSC. Currently processing 486,972 live data streams, analyzing $11.4 billion in daily transaction volume, and tracking 129,102 high value bridges.

Detection Methodology

E0G analyzes transactions across multiple dimensions: amount, timing, network location, wallet behavior, and bridge interactions. When evaluating suspicious activity, the system examines:

• Transaction timing relative to bridge confirmations

• Wallet addresses in cross chain transfers

• Smart contract method calls

• State changes in related contracts

• Historical wallet behavior patterns

Multi dimensional tensor mathematics identifies exploit signatures by processing these factors simultaneously rather than sequentially. Matches or significant deviations generate alerts with confidence scores.

Technical Architecture

Block Indexing 279GB database with 9.5 million indexed blocks containing transaction details, smart contract interactions, and cross chain bridge activity.

Pattern Recognition Identifies 225+ suspicious patterns daily with 7.0/7 average confidence. Combines signature matching with anomaly detection.

AI Integration Analyzes multi step attacks that spread across networks by examining wallet interactions over time rather than isolated transactions.

Cross Chain Correlation Tracks fund movements between chains and detects when transactions split across networks to evade single chain detection.

Detected Vulnerabilities

MethodID Replay Attack Pattern: methodID 0xd366bcc2 appearing in cross chain transactions with characteristics allowing multiple fund extractions Risk: Transaction replay enabling repeated withdrawals.

Proxy Implementation Mismatch Contracts: 0x6866B4923fc3Fe89ac10b3eF0aB7e9eF5fC00dCA (proxy) and 0x511835d52F6A89f39499F8ff35a1341EA53cb93e (implementation) Issue: Function delegation allowing unauthorized access to protected methods Detection: State change patterns inconsistent with expected proxy behavior.

Reentrancy Pattern Contract: 0x890FD716Cf80B5f9D3CdA34Fc6b1C67CBb2d35c3 Pattern: External calls preceding state changes in high value transactions Matches signature of known reentrancy exploits.

Real Time Performance

• Transactions and patterns analyzed continuously

• 99.9%+ uptime over 90+ days

• Sub 500ms API response time

Continuous operation with automated failover. Critical detections trigger detailed logging including contract addresses, method signatures, and cross chain correlations.

Technical Scope

Monitors EVM compatible networks. Identifies suspicious activity and provides intelligence for security teams. AI learns normal behavior to reduce false positives.

API Access

REST endpoints provide transaction details, pattern classifications, and confidence scores. Enterprise clients receive webhook notifications for high priority detections.