This paper provides the first comprehensive study of cryptographic API misuse detection in Go, evaluating four state-of-the-art tools and discovering 7,473 instances of cryptographic API misuses acros…

The paper analyzes a large dataset of JavaScript packages to demonstrate that a small number of vulnerable dependencies can propagate vulnerabilities across a disproportionately large number of packag…

The paper introduces PVAC, a novel victim-based row counting mechanism that accurately tracks RowHammer attacks by incrementing counters on the victim row, thereby improving hammering tolerance and pe…

The paper analyzes the bit-flip vulnerability of shared KV-cache blocks in LLM serving systems, demonstrating that these blocks are susceptible to silent, persistent, and selective data corruption.

LIPPEN introduces a novel hardware-software co-design that provides strong, zero-overhead pointer encryption for enhanced memory safety, achieving comprehensive pointer integrity and confidentiality.

This paper introduces a novel class of backdoor attacks that exploit the numerical side effects of LLM inference optimization, achieving high success rates while maintaining clean accuracy.

The paper introduces HarmChip, a novel benchmark to evaluate LLM vulnerability to domain-specific hardware security threats, revealing that current safety guardrails fail against semantically disguise…

The paper introduces SymTEE, an LLM-assisted symbolic execution framework that detects missing input validation vulnerabilities in TEE applications without needing complex, real TEE setups.

The paper proposes Rowhammer Vulnerability Counter (RVC), a novel framework that improves RowHammer mitigation by tracking a row's actual vulnerability to bit flips rather than relying on simple activ…

The paper systematically evaluates various defense mechanisms against persistent memory attacks on LLM agents, finding that only tool-gating at the memory layer (Memory Sandbox) effectively mitigates…

The paper proposes a novel symbolic execution technique that combines speculative library preloading and custom software hooks to recover Control Flow Graphs (CFGs) from binaries that use dynamic code…

SeqShield proposes a behavior-based rootkit detection system for Windows by analyzing API call sequences using n-gram features, achieving high detection accuracy even against mutated malware variants.

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 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…

This paper conducts a large-scale empirical study demonstrating that Java library exploits can accurately identify affected versions, achieving high recall and precision, and proposes strategies for e…

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 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…

This paper presents SCP, a cache partitioning design that combines strict eviction isolation with write-shared coherence to mitigate eviction-based cache side channels.

The paper introduces EXHIB, a comprehensive benchmark of five real-world datasets, to evaluate Function Similarity Detection, demonstrating that current models fail to generalize across diverse low- a…

The paper introduces a provenance-aware vulnerability analysis approach that accurately identifies cross-ecosystem vulnerabilities in Python applications by resolving vendored native libraries to spec…