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

GbyAI
GbyAI
Blog — PlanetScale
Blog — PlanetScale
The GitHub Blog
The GitHub Blog
Microsoft Security Blog
Microsoft Security Blog
I
InfoQ
A
About on SuperTechFans
T
The Blog of Author Tim Ferriss
D
DataBreaches.Net
L
LangChain Blog
F
Fortinet All Blogs
C
Check Point Blog
Google DeepMind News
Google DeepMind News
云风的 BLOG
云风的 BLOG
Engineering at Meta
Engineering at Meta
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
H
Help Net Security
J
Java Code Geeks
月光博客
月光博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
IT之家
IT之家
aimingoo的专栏
aimingoo的专栏
小众软件
小众软件
宝玉的分享
宝玉的分享
Jina AI
Jina AI

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
A Longitudinal Study on Web-sites Password Management (in...
Simone Raponi, Roberto Di Pietro · 2019-11-17 · via cs.CR updates on arXiv.org

Single-factor password-based authentication is generally the norm to access on-line Web-sites. While single-factor authentication is well known to be a weak form of authentication, a further concern arises when considering the possibility for an attacker to recover the user passwords by leveraging the loopholes in the password recovery mechanisms. Indeed, the adoption by a Web-site of a poor password management system makes useless even the most robust password chosen by the registered users. In this paper, building on the results of our previous work, we study the possible attacks to on-line password recovery systems analyzing the mechanisms implemented by some of the most popular Web-sites. In detail, we provide several contributions: (i) we revise and detail the attacker model; (ii) we provide an updated analysis with respect to a preliminary study we carried out in December 2017; (iii) we perform a brand new analysis of the current top 200 Alexa's Web-sites of five major EU countries; and, (iv) we propose \sol, a working open-source module that could be adopted by any Web-site to provide registered users with a password recovery mechanism to prevent mail service provider-level attacks. Overall, it is striking to notice how the analyzed Web-sites have made little (if any) effort to become compliant with the GDPR regulation, showing that the objective to have basic user protection mechanisms in place---despite the fines threatened by GDPR---is still far, mainly because of sub-standard security management practices. Finally, it is worth noting that while this study has been focused on EU registered Web-sites, the proposed solution has, instead, general applicability.