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cs.CR updates on arXiv.org

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
Quantifying the Impact of Stealthy BLE Spam & Flooding At...
[Submitted on 19 Jun 2026] · 2026-06-23 · via cs.CR updates on arXiv.org

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Abstract:The energy-efficient design of the BLE protocol, emphasis on rapid, and userfriendly discovery, making it an ideal choice for IoMTs, specifically, military field medical systems, and battlefield wearable sensors. Especially in active conflict zones, when static medical facilities are vulnerable and often targeted, limiting their viability for sustained care delivery. This rapid deployment, and ease of management comes at the cost of expanded attack surface, i.e., BLE flooding attacks. During such attacks, adversaries flood advertisement channels with unauthorized connection or advertising requests to exhaust nearby device resources and disrupt legitimate communication, sometimes culminating in denial-of-service conditions. A first public proof-of-concept of such attacks, using a Raspberry Pi has since been adapted to commodity platforms (e.g., Flipper Zero, HackRF, Android), lowering the barrier to attack. In contested environments, such platforms are directly relevant to adversarial RF jamming and spoofing operations, where low-cost, portable devices can induce disproportionate disruption in dense wireless ecosystems. In this work, we develop a quantitative foundation for understanding the impact of such attacks and propose a practical deterrence strategy based on agility to raise the cost of such attacks.

Submission history

From: Usman Rauf [view email]
[v1] Fri, 19 Jun 2026 01:01:09 UTC (910 KB)