GenDetect introduces a novel framework to rapidly generalize detection rules from single observed DeFi exploits, significantly improving resilience against subsequent, similar 'Imitative Attack Cascad…

UniDetect is a novel LLM-driven method that detects cross-chain cryptocurrency fraud by generating generalized transaction summaries, significantly outperforming existing detection techniques across m…

The paper demonstrates that current transfer-based AML systems fail in complex DeFi environments because economic value migration can be structurally decoupled from explicit token transfers.

LibScan is an automated framework that detects eight categories of smart contract library misuse by combining LLM-based semantic reasoning with rule-based analysis, achieving 85.15% accuracy on real-w…

The paper introduces the Lean-Agent Protocol, a formal verification platform that uses Lean 4 theorem proving to ensure agentic AI actions in finance are mathematically compliant with complex regulati…

The paper introduces Deniable Covert Asset Transfer (DCAT), a method that stages asset transfers to appear as ordinary, loss-producing DeFi activities, achieving empirical unobservability on major blo…

This paper proposes TrapHunter, a framework to identify deceptive trap tokens in standardized contracts using intent deviation analysis and dynamic validation.

GoAT-X introduces a novel framework that structures cross-chain smart contract auditing as a Graph of Auditing Thoughts, significantly improving the detection of complex, semantic vulnerabilities in m…

The paper introduces Sentinel, a novel proxy-based system that achieves comprehensive, type-agnostic reentrancy protection for smart contracts by intercepting all external calls.

This paper analyzes the x402 payment protocol, revealing systemic vulnerabilities in state synchronization and signature design that allow attackers to exploit payment systems for resource leakage in…

This paper analyzes the x402 payment protocol, revealing critical synchronization and security flaws that allow attackers to exploit payment systems and force merchants to subsidize compute costs.

The paper introduces SST-Guard, a multi-modal browser-based system that detects and blocks server-side Google Analytics (sGA) by identifying the semantic patterns of collected data rather than relying…

SCAFDS introduces a novel, seven-stage graph attention system that models fraud propagation using co-occurrence edge features and generates forensically traceable SAR narratives, significantly improvi…

The paper analyzes and documents various double-dip reward abuse attacks that exploit flaws in how cashback and reward engines handle transaction refunds, proposing formal invariants and defensive alg…

The paper analyzes the nascent DeFi investment agent market, finding that while token valuations are high, current deployments are heterogeneous, lack clear autonomous execution, and exhibit poor risk…

The paper empirically analyzes the nascent DeFi investment agent market, finding that while token valuations are high, current deployments lack robust autonomous execution and exhibit poor risk-adjust…

The paper demonstrates that large language models (LLMs) exhibit measurable, controllable biases toward specific assets like Bitcoin, identifying an internal feature that can causally shift portfolio…

LiquiLM is a novel framework that combines Large Language Models (LLMs) with a Dynamic Co-Attention Network (DCN) to effectively bridge the semantic gap between complex smart contract code and high-le…

The paper introduces Bitcoin Smart Accounts (BSA), a novel, trust-minimized protocol enabling native Bitcoin to participate in DeFi while maintaining self-custody of funds.