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cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Open Source, Open Threats? Investigating Security Challen...
Seyed Ali Akhavani, Behzad Ousat, Amin Kharraz · 2025-06-16 · via cs.CR updates on arXiv.org

Open-source software (OSS) has become increasingly more popular across different domains. However, this rapid development and widespread adoption come with a security cost. The growing complexity and openness of OSS ecosystems have led to increased exposure to vulnerabilities and attack surfaces. This paper investigates the trends and patterns of reported vulnerabilities within OSS platforms, focusing on the implications of these findings for security practices. To understand the dynamics of OSS vulnerabilities, we analyze a comprehensive dataset comprising 31,267 unique vulnerability reports from GitHub's advisory database and Snyk.io, belonging to 14,675 packages across 10 programming languages. Our analysis reveals a significant surge in reported vulnerabilities, increasing at an annual rate of 98%, far outpacing the 25% average annual growth in the number of open-source software (OSS) packages. Additionally, we observe an 85% increase in the average lifespan of vulnerabilities across ecosystems during the studied period, indicating a potential decline in security. We identify the most prevalent Common Weakness Enumerations (CWEs) across programming languages and find that, on average, just seven CWEs are responsible for over 50% of all reported vulnerabilities. We further examine these commonly observed CWEs and highlight ecosystem-specific trends. Notably, we find that vulnerabilities associated with intentionally malicious packages comprise 49% of reports in the NPM ecosystem and 14% in PyPI, an alarming indication of targeted attacks within package repositories. We conclude with an in-depth discussion of the characteristics and attack vectors associated with these malicious packages.