VulDec: Vulnerability Detection in Binaries via Neural Decompilation
Automated vulnerability detection in binary executables is challenging due to the lack of source code and the limited se
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← 返回所有主题Can Agentic Code Review Catch Vulnerabilities Before They Are Merged?
LLM agents have been increasingly adopted for security-focused code review, but existing benchmarks mostly derive the re
Secure and Functional Code Generation with Self-Evaluation
Large Language Models (LLMs) can generate functionally correct code that remains insecure. Security-focused fine-tuning
Trusting the Tool: Asymmetric Deference of LLM Vulnerability Auditors to Static-Analysis Evidence
Pipelines that combine large language models (LLMs) with static analysis let the model consume the analyser's output as
DeepAVR: Deep Analysis via Multi-Agent Collaboration for Automated Vulnerability Repair
Automated Vulnerability Repair (AVR) has emerged as a critical defense against software security flaws, aiming to triage
Ulysses: A Security Harness For Synthesizing Verifiable Web Exploits
How can an AI agent automatically discover security vulnerabilities in any software repository? Existing approaches use
Can Loan Processors and Underwriters Spot AI-Edited Statements? An Empirical Study
AI-assisted editing can produce loan documents that preserve familiar issuer layouts while changing the applicant's iden
JANUS: Agentic Cross-Language Fuzzing Harness Generation for Android Native Libraries
Modern Android apps extensively rely on native libraries, bridging Java/Kotlin and C/C++ through the Java Native Interfa
CertMoE: Robustness Certification for Mixture-of-Experts LLMs via Routing-Aware Smoothing
Provable robustness is a cornerstone of trustworthy machine learning, aiming to guarantee model predictions under advers
How Much Does the Harness Matter, and for Whom? A Multi-Model Study of Context in LLM-Driven Vulnerability Discovery
How much does an agent harness affect vulnerability discovery, and does its value depend on the model? We study 24 model
Sign Here: Attributing a Source for a More Trustworthy Software Supply Chain
Software supply chain attacks continue to be on the rise, exploiting the trust that helps open source ecosystems thrive.
Self-Evolving Static Analysis via LLM Pseudo-Labeling
Security bugs often slip past static analysis not because they are impossible to detect, but because detection rules hav
Raise or Check? Predicting the Necessity of Additional Fuzzing for Continuous Fuzzing
Continuous fuzzing is used for vulnerability detection in Open Source Software (OSS). Large-scale services such as Googl
AgenticVulHunter: Bringing Local Agentic Vulnerability Hunting to Your Terminal
Finding vulnerabilities early, before they can affect the production system, is important for reducing the risk of any s
A Hybrid Information Flow Analysis Framework for Android Hybrid Apps
The WebView interface in Android (hybrid) applications enables the native side (e.g., Java) to exchange data with the We
SPLASH: Contrastive Audit Pressure for Detecting and Localizing Security Hallucinations in Generated Code
Code generated by large language models often passes every functional test while remaining insecure. These security hall
How Effectively Do Security Skills Guide Coding Agents in Vulnerability Detection in Linux Kernel?
Large language model (LLM) coding agents, such as Claude Code, are increasingly used for security auditing, with task-sp
Many Repairs, One Direction: Steering Code Models Toward Safer Cryptographic API Use
Cryptographic API misuse in large language model-generated code can compromise software security. While many existing ap
CAT-RAG: Improving Secure Code Generation with Category-Aware Agentic Retrieval
Despite rapid progress in LLM-based code generation, security vulnerabilities remain widespread, and retrieval-augmented
Narratives Mislead: An Empirical Study of How LLMs Misjudge CVSS Severity in Bug Bounty Reports
Bug bounty platforms receive vulnerability reports faster than vendors can triage them, and Large Language Models (LLMs)