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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
On the Prevalence and Usage of Commit Signing on GitHub: ...
Anupam Sharma, Sreyashi Karmakar, Gayatri Priyadarsini Kancherla · 2025-04-27 · via cs.CR updates on arXiv.org

GitHub is one of the most widely used public code development platform. However, the code hosted publicly on the platform is vulnerable to commit spoofing that allows an adversary to introduce malicious code or commits into the repository by spoofing the commit metadata to indicate that the code was added by a legitimate user. The only defense that GitHub employs is the process of commit signing, which indicates whether a commit is from a valid source or not based on the keys registered by the users. In this work, we perform an empirical analysis of how prevalent is the use of commit signing in commonly used GitHub repositories. To this end, we build a framework that allows us to extract the metadata of all prior commits of a GitHub repository, and identify what commits in the repository are verified. We analyzed 60 open-source repositories belonging to four different domains -- web development, databases, machine learning and security -- using our framework and study the presence of verified commits in each repositories over five years. Our analysis shows that only ~10% of all the commits in these 60 repositories are verified. Developers committing code to security-related repositories are much more vigilant when it comes to signing commits by users. We also analyzed different Git clients for the ease of commit signing, and found that GitKraken provides the most convenient way of commit signing whereas GitHub Web provides the most accessible way for verifying commits. During our analysis, we also identified an unexpected behavior in how GitHub handles unverified emails in user accounts preventing legitimate owner to use the email address. We believe that the low number of verified commits may be due to lack of awareness, difficulty in setup and key management. Finally, we propose ways to identify commit ownership based on GitHub's Events API addressing the issue of commit spoofing.