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On the Security of Research Artifacts SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety 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 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
ParsEval: Evaluation of Parsing Behavior using Real-world...
Stefan Tatschner, Sebastian N. Peters, Michael P. Heinl, Tobias · 2024-05-29 · via cs.CR updates on arXiv.org

X.509 certificates play a crucial role in establishing secure communication over the internet by enabling authentication and data integrity. Equipped with a rich feature set, the X.509 standard is defined by multiple, comprehensive ISO/IEC documents. Due to its internet-wide usage, there are different implementations in multiple programming languages leading to a large and fragmented ecosystem. This work addresses the research question "Are there user-visible and security-related differences between X.509 certificate parsers?". Relevant libraries offering APIs for parsing X.509 certificates were investigated and an appropriate test suite was developed. From 34 libraries 6 were chosen for further analysis. The X.509 parsing modules of the chosen libraries were called with 186,576,846 different certificates from a real-world dataset and the observed error codes were investigated. This study reveals an anomaly in wolfSSL's X.509 parsing module and that there are fundamental differences in the ecosystem. While related studies nowadays mostly focus on fuzzing techniques resulting in artificial certificates, this study confirms that available X.509 parsing modules differ largely and yield different results, even for real-world out-in-the-wild certificates.