105 matches found
CVE-2026-103974 lichess.org: Stored HTML Injection via PGN Annotator Tag in Studies
lichess.org is the forever free, adless and open source chess server. Prior to commit c54596c9e1569d378fe20f80d4c790c6fdee54c4, a user who can add a chapter to a study can place attacker-controlled text in the PGN Annotator tag, which becomes Comment.Author.External and is returned verbatim by...
Cloud-Penetration-Testing-Guide
☁️ Cloud Penetration Testing Guide - Completo Guia operaciona...
A SoK for SoCs: Reading the TI Leaves on AI for Cyber Threat Intelligence Generation and Sharing
Cyber Threat Intelligence CTI is essential for defending mission-critical infrastructure, yet the process of transforming raw attack evidence into shareable CTI remains fragmented and understudied. We conduct a literature survey of academic papers, organizing the CTI lifecycle into three stages:...
A Meta-Study on Replication Papers in Usable Security and Privacy
The field of usable security and privacy research is a young and expanding field, which is still developing standards for its research, e.g. regarding replications. We used a mixed-method approach, in order to get a better understanding of the current state of replications in the field of usable...
A Controlled Candidate-Set Benchmark for Offline Satellite-Security Plan Decomposition
Some security-development settings require local models that map an objective to an ordered, checkable plan. We present a low-rank decomposition adapter and release a case-disjoint corpus with 24 authored decompositions and 83 derived next-step examples across 24 satellite-security cases. To...
Google and Microsoft Pull ModHeader With 1.6 Million Installs After Dormant Collector Found
Google and Microsoft have pulled ModHeader , a popular header-editing extension with roughly 1.6 million installs across Chrome and Edge, after researchers found a hidden browsing-history collector built into its official store version. The collector was dormant. An empty allow-list kept it...
Large Language Models (LLMs) and Generative AI in Cybersecurity and Privacy: A Survey of Dual-Use Risks, AI-Generated Malware, Explainability, and Defensive Strategies
Large Language Models LLMs and generative AI GenAI systems, such as ChatGPT, Claude, Gemini, LLaMA, Copilot, Stable Diffusion by OpenAI, Anthropic, Google, Meta, Microsoft, Stability AI, respectively, are revolutionizing cybersecurity, enabling both automated defense and sophisticated attacks...
Rising from the Ashes: How Agentic AI Is Unblocking Challenges in Cybersecurity
Security remains a high-cost challenge, with many problems historically deemed inefficient to address or effectively unsolvable. A significant number of these problems stem from labor-intensive tasks that create bottlenecks in defensive approaches. Agentic AI has the potential to alleviate these...
Obliv-Clang: Real-World Oblivious Programming in C++
Side-channel vulnerabilities, particularly timing and access-pattern-based attacks, have become critical issues for confidential data processing in trusted environments. Oblivious programming is an effective approach to alleviate these attacks by making program execution not leak any secret throu...
Credential Disclosure in (EU) Digital Identity Wallets: Privacy Risks and Practical Mitigations
The European Union will introduce the EUDI Wallet by late 2026, which allows users to hold digital credentials i.e., representations of physical official identity documents on their devices. This will allow users to securely and privately disclose identity attributes to websites. Although such a...
CRESS: Quantifying Vulnerabilities of Attack Scenarios in Hardware Reverse Engineering
The safety, security, and reliability of microelectronic systems depend on a trustworthy, secured supply chain and design flow. Globally distributed supply chains or unintentional design weaknesses leave the door open for attacks on the hardware level. These scenarios encompass counterfeiting,...
Do You Dare to Try Test-Driven Forensics? Increasing Trust in Desktop Forensics with ADARE
Digital forensic relies on validated tools and established procedures, yet the underlying operating systems, applications, and analysis tools evolve rapidly. This evolution can cause artifact behavior and tool outputs to drift, silently degrading repeatability and confidence in long-lived forensi...
SAMD: A Tool for Identifying False Data Injection Scenarios in AI/ML-Enabled Medical Devices
The growing integration of artificial intelligence AI and machine learning ML in medical systems requires effective measures to address emerging security risks. One such risk is that of adversaries introducing false data through vulnerable system components during inference, causing misdiagnosis...
Building an Adversarial Malware Dataset by Family and Type: Generation, Evasion, and Poisoning Evaluation
We present a dataset of adversarial malware samples derived from the public RawMal-TF collection of real-world malware binaries. Using a suite of adversarial malware generators, we construct two sets of adversarial PE files: 44,347 family-labelled samples and 33,596 type-labelled samples, achievi...
portofolio_DWForSec
DwF — Cybersecurity Portfolio A professional cybersecurity po...
Converging Zero Trust and IoT Security: A Multivocal Literature Review
The convergence of Internet of Things IoT security and Zero Trust ZT principles is a trending topic, demanding a comprehensive, multi-perspective analysis. We present the first multivocal literature review MLR on this topic, combining 68 academic and 36 industrial studies. This comprehensive revi...
Mythos and the Unverified Cage: Z3-Based Pre-Deployment Verification for Frontier-Model Sandbox Infrastructure
The April 2026 Claude Mythos sandbox escape exposed a critical weakness in frontier AI containment: the infrastructure surrounding advanced models remains susceptible to formally characterizable arithmetic vulnerabilities. Anthropic has not publicly characterized the escape vector; some secondary...
Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain
Large language model LLM agents increasingly rely on third-party API routers to dispatch tool-calling requests across multiple upstream providers. These routers operate as application-layer proxies with full plaintext access to every in-flight JSON payload, yet no provider enforces cryptographic...
Software Vulnerability Detection Using a Lightweight Graph Neural Network
Large Language Models LLMs have emerged as a popular choice in vulnerability detection studies given their foundational capabilities, open source availability, and variety of models, but have limited scalability due to extensive compute requirements. Using the natural graph relational structure o...