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VLA Foundry: A Unified Framework for Training Vision-Language-Action Models Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning Neurosymbolic Repo-level Code Localization CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Verification Modulo Tested Library Contracts The Semi-Executable Stack: Agentic Software Engineering and the Expanding Scope of SE Scaling Test-Time Compute for Agentic Coding AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgment From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks Prompt-Driven Code Summarization: A Systematic Literature Review LinuxArena: A Control Setting for AI Agents in Live Production Software Environments LLMs taking shortcuts in test generation: A study with SAP HANA and LevelDB Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go? Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment
Investigating Vulnerability Disclosures in Open-Source So...
Jessy Ayala, Yu-Jye Tung, Joshua Garcia · 2025-01-30 · via cs.SE updates on arXiv.org

In the world of open-source software (OSS), the number of known vulnerabilities has tremendously increased. The GitHub Advisory Database contains advisories for security risks in GitHub-hosted OSS projects. As of 09/25/2023, there are 197,609 unreviewed GitHub security advisories. Of those unreviewed, at least 63,852 are publicly documented vulnerabilities, potentially leaving many OSS projects vulnerable. Recently, bug bounty platforms have emerged to focus solely on providing bounties to help secure OSS. In this paper, we conduct an empirical study on 3,798 reviewed GitHub security advisories and 4,033 disclosed OSS bug bounty reports, a perspective that is currently understudied, because they contain comprehensive information about security incidents, e.g., the nature of vulnerabilities, their impact, and how they were resolved. We are the first to determine the explicit process describing how OSS vulnerabilities propagate from security advisories and bug bounty reports, which are the main intermediaries between vulnerability reporters, OSS maintainers, and dependent projects, to vulnerable OSS projects and entries in global vulnerability databases and possibly back. This process uncovers how missing or delayed CVE assignments for OSS vulnerabilities result in projects, both in and out of OSS, not being notified of necessary security updates promptly and corresponding bottlenecks. Based on our findings, we provide suggestions, actionable items, and future research directions to help improve the security posture of OSS projects.