The paper proposes a tamper-proofing model for self-modifying code (SMC) by leveraging external timing, concurrency, and microarchitectural state to make non-SMC reproduction detectably expensive.

Janus is a compiler-based security framework for ARM64 that mitigates transient execution attacks like Spectre by integrating PA and BTI microarchitectural features, achieving strong security with low…

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…

The paper introduces SCAgent, an automated framework that uses LLM-assisted agents to systematically discover, analyze, and assess side-channel leakage risks in complex systems like iOS, moving beyond…

QCIVET introduces a novel contract-based framework to ensure the integrity of hybrid quantum-classical pipelines by verifying both the structure (syntactic) and the behavior (semantic) of quantum stag…

Veritas is a semantically grounded framework that detects memory corruption vulnerabilities in stripped binaries by combining static analysis, LLM-based reasoning, and runtime validation, achieving hi…

The paper introduces a novel multi-LLM orchestration system combined with symbolic execution to successfully detect memory vulnerabilities in uncompilable, incomplete Rust CVE code snippets, achieving…

SAILOR automates the construction of symbolic execution harnesses by combining static analysis and LLM-based synthesis, significantly improving the scalability and effectiveness of vulnerability disco…

The paper introduces a novel memory forensics framework to perform runtime analysis of Go malware, successfully recovering critical execution state and artifacts that are invisible to traditional stat…

MemHint is a neuro-symbolic static analysis pipeline that significantly improves memory leak detection in C/C++ by combining LLM semantic understanding with Z3 symbolic reasoning, detecting more leaks…

The paper introduces TLSCheck 2.0, an enhanced memory forensics plugin for Volatility 3, designed to efficiently detect and analyze suspicious TLS callbacks in process memory.

The paper proposes a general, compiler-integrated framework for secure content composition that minimizes the syntactic difference between secure and insecure coding practices.

This study formally verified 3,500 AI-generated code artifacts and found that a majority (55.8%) contain exploitable security vulnerabilities, regardless of the LLM used.

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…

The paper introduces PoSME, a cryptographic primitive that enforces strict sequential memory execution by chaining data-dependent writes, providing verifiable delay and authorship attestation.

The paper introduces BOUNDARY FLOW, an LLVM-based framework that enhances kernel fuzzing and analysis by extracting per-task, state-aware data-flow information (arguments and return values) at functio…

The paper analyzes LLM vulnerability detection using mechanistic interpretability, finding that models primarily rely on safety detectors rather than direct vulnerability signature recognition.

NeuroLog is a novel, build-free neuro-symbolic pipeline that combines LLM-derived dataflow facts, Datalog, and SMT solving to systematically discover and synthesize exploitable memory safety vulnerabi…

PoisonCap introduces a new 'poison' capability format for CHERI systems to provide efficient, strict use-after-free and initialization safety, surpassing existing temporal safety solutions.

The paper introduces uGen, the first LLM-driven framework that uses a retrieval-augmented, multi-agent design to automatically generate functionally correct microarchitectural attack Proof-of-Concepts…