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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
Post-Quantum Signatures in DNSSEC via Request-Based Fragm...
Jason Goertzen, Douglas Stebila · 2022-11-25 · via cs.CR updates on arXiv.org

The Domain Name System Security Extensions (DNSSEC) provide authentication of DNS responses using digital signatures. DNS operates primarily over UDP, which leads to several constraints: notably, packets should be at most 1232 bytes long to avoid problems during transmission. Larger DNS responses either need to be fragmented into several UDP responses or the request would need to be repeated over TCP, neither of which is sufficiently reliable in today's DNS ecosystem. While RSA or elliptic curve digital signatures are sufficiently small to avoid this problem, even for DNSSEC packets containing both a public key and a signature, this problem is unavoidable when considering the larger sizes of post-quantum schemes. We propose ARRF, a method of fragmenting DNS resource records at the application layer (rather than the transport layer) that is request-based, meaning the initial response contains a truncated fragment and then the requester sends follow-up requests for the remaining fragments. Using request-based fragmentation avoids problems identified for several previously proposed (and rejected) application-level DNS fragmentation techniques. We implement our approach and evaluate its performance in a simulated network when used for the three post-quantum digital signature schemes selected by NIST for standardization (Falcon, Dilithium, and SPHINCS+) at the 128-bit security level. Our experiments show that our request-based fragmentation approach provides substantially lower resolution times compared to standard DNS over UDP with TCP fallback, for all the tested post-quantum algorithms, and with less data transmitted in the case of both Falcon and Dilithium. Furthermore, our request-based fragmentation design can be implemented relatively easily: our implementation is in fact a small daemon that can sit in front of a DNS name server or resolver to fragment/reassemble transparently.