惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

U
Unit 42
小众软件
小众软件
Y
Y Combinator Blog
S
SegmentFault 最新的问题
WordPress大学
WordPress大学
宝玉的分享
宝玉的分享
人人都是产品经理
人人都是产品经理
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
L
LangChain Blog
Martin Fowler
Martin Fowler
美团技术团队
B
Blog RSS Feed
GbyAI
GbyAI
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
大猫的无限游戏
大猫的无限游戏
博客园 - 司徒正美
T
Tailwind CSS Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
T
The Blog of Author Tim Ferriss
Microsoft Azure Blog
Microsoft Azure Blog
腾讯CDC
Hugging Face - Blog
Hugging Face - Blog
D
Docker
G
Google Developers Blog

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
Optimizing Password Cracking for Digital Investigations
Mohamad Hachem, Adam Lanfranchi, Nathan Clarke, Joakim Kavrestad · 2025-04-04 · via cs.CR updates on arXiv.org

Efficient password cracking is a critical aspect of digital forensics, enabling investigators to decrypt protected content during criminal investigations. Traditional password cracking methods, including brute-force, dictionary and rule-based attacks face challenges in balancing efficiency with increasing computational complexity. This study explores rule based optimisation strategies to enhance the effectiveness of password cracking while minimising resource consumption. By analysing publicly available password datasets, we propose an optimised rule set that reduces computational iterations by approximately 40%, significantly improving the speed of password recovery. Additionally, the impact of national password recommendations were examined, specifically, the UK National Cyber Security Centre's three word password guideline on password security and forensic recovery. Through user generated password surveys, we evaluate the crackability of three word passwords using dictionaries of varying common word proportions. Results indicate that while three word passwords provide improved memorability and usability, they remain vulnerable when common word combinations are used, with up to 77.5% of passwords cracked using a 30% common word dictionary subset. The study underscores the importance of dynamic password cracking strategies that account for evolving user behaviours and policy driven password structures. Findings contribution to both forensic efficiency and cyber security awareness, highlight the dual impact of password policies on security and investigative capabilities. Future work will focus upon refining rule based cracking techniques and expanding research on password composition trends.