This paper evaluates modern reentrancy detection tools, finding that leading LLMs significantly outperform most existing static analyzers and ML models on both real-world and handcrafted benchmarks.

The paper provides the first machine-checked, tridirectional correctness proof of the OpenZeppelin reentrancy-guard pattern against complex, production-deployed Solidity smart contract source.

Grimlock is an Agent Guard that enhances security for high-agency systems by enforcing identity, authorization, and scope-bound communication through eBPF and attested TLS channels, without modifying…

SCARA is a novel, end-to-end framework that autonomously connects binary-level vulnerability candidates to conditionally validated remedies for opaque industrial software, achieving high precision and…

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…

WATSON is a novel, efficient shadow stack protection mechanism for embedded systems that utilizes standard hardware data watchpoints to mitigate control-flow hijacking vulnerabilities without relying…

The paper introduces Heimdall, an automated pipeline that uses LLMs and formal verification to safely and automatically migrate legacy, potentially buggy eBPF programs written in C to memory-safe Rust…

This paper systematically analyzes the threat posed by malicious third-party API routers in the LLM supply chain, finding that a significant number of routers actively perform payload injection, crede…

The paper introduces an AI red teaming agent that drastically reduces the time and effort required for security testing by allowing operators to define complex attack goals using natural language, com…

The paper introduces Distributed Sentinel, a zero-trust architecture that prevents Context-Fragmented Violations (CFVs) in multi-agent systems by propagating security state across departmental boundar…

AttackPathGNN proposes a novel graph neural network approach to detect smart contract vulnerabilities by modeling explicit attack paths and function interactions, achieving high detection rates on sta…

PropGuard introduces a propagation-aware framework to safeguard LLM-MAS against malicious attacks by constructing a dual-view graph, identifying suspicious propagation paths, and applying source-guide…

The paper introduces Constraint-Guided Semantic Testing (ConSeT), a novel framework that systematically finds critical, pre-authentication vulnerabilities in 5G User Equipment (UE) by exploiting seman…

AgentVisor is a novel defense framework that uses semantic virtualization, inspired by OS principles, to significantly reduce LLM agent vulnerability to prompt injection while maintaining high utility…

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.

The paper introduces an efficient, lightweight LLM framework for smart contract auditing that decouples the audit process into multiple components, achieving high accuracy while significantly reducing…

VIPER-MCP is a novel, end-to-end automated framework that detects and dynamically confirms the exploitability of taint-style vulnerabilities in Model Context Protocol (MCP) servers, achieving high-fid…

The paper introduces PSR extsuperscript{2}, a novel static analysis framework that significantly improves the detection of atomicity violations in smart contracts by combining structural path searchin…

RegGuard is a unified framework that enhances optimistic rollups with three coordinated mechanisms—semantic validation, cross-layer state consistency checks, and fair ordering—to make them suitable fo…

The paper proposes a canonical, end-to-end validation framework to ensure secure integration of Alternative Data Availability (AltDA) systems with Ethereum Layer 2s, demonstrating that L2 integration…