Threat modeling AI applications

Proactively identifying, assessing, and addressing risk in AI systems We cannot anticipate every misuse or emergent behavior in AI systems. We can , however, identify what can go wrong, assess how bad it could be, and design systems that help reduce the likelihood or impact of those failure modes...

How to Organize Safely in the Age of Surveillance

From threat modeling to encrypted collaboration apps, we’ve collected experts’ tips and tools for safely and effectively building a group—even while being targeted and tracked by the powerful...

The Rise of AI Agent Communities: Large-Scale Analysis of Discourse and Interaction on Moltbook

Moltbook is a Reddit-like social platform where AI agents create posts and interact with other agents through comments and replies, offering a real-world setting to examine agent-to-agent communication at scale. Using a public API snapshot collected about five days after launch 122,438 posts, we...

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP

The rapid development of the AI agent communication protocols, including the Model Context Protocol MCP, Agent2Agent A2A, Agora, and Agent Network Protocol ANP, is reshaping how AI agents communicate with tools, services, and each other. While these protocols support scalable multi-agent...

[SECURITY] Fedora 42 Update: plantuml-1.2026.1-1.fc42

PlantUML is a program allowing to draw UML diagrams, using a simple and human readable text description. It is extremely useful for code documenting, sketching project architecture during team conversations and so on. PlantUML supports the following diagram types - sequence diagram - use case...

SoK: The Pitfalls of Deep Reinforcement Learning for Cybersecurity

Deep Reinforcement Learning DRL has achieved remarkable success in domains requiring sequential decision-making, motivating its application to cybersecurity problems. However, transitioning DRL from laboratory simulations to bespoke cyber environments can introduce numerous issues. This is furthe...

Reference-Free EM Validation Flow for Detecting Triggered Hardware Trojans

Hardware Trojans HTs threaten the trust and reliability of integrated circuits ICs, particularly when triggered HTs remain dormant during standard testing and activate only under rare conditions. Existing electromagnetic EM side-channel-based detection techniques often rely on golden references o...

Toward Risk Thresholds for AI-Enabled Cyber Threats: Enhancing Decision-Making under Uncertainty with Bayesian Networks

Artificial intelligence AI is increasingly being used to augment and automate cyber operations, altering the scale, speed, and accessibility of malicious activity. These shifts raise urgent questions about when AI systems introduce unacceptable or intolerable cyber risk, and how risk thresholds...

CVE-2011-0792

Unspecified vulnerability in the Oracle Warehouse Builder component in Oracle Database Server 10.2.0.5 OWB and 11.1.0.7 allows remote authenticated users to affect confidentiality, integrity, and availability via unknown vectors related to Dimensional Data Modeling...

Supporting Secured Integration of Microarchitectural Defenses

There has been a plethora of microarchitectural-level attacks leading to many proposed countermeasures. This has created an unexpected and unaddressed security issue where naive integration of those defenses can potentially lead to security vulnerabilities. This occurs when one defense changes an...

Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturing

Additive manufacturing AM is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical convergence introduces new attack surfaces, especially at the interface between computer-aided design CAD and machine execution layers. In this work, ...

Neutralization of IMU-Based GPS Spoofing Detection Using External IMU Sensor and Feedback Methodology

Autonomous Vehicles AVs refer to systems capable of perceiving their states and moving without human intervention. Among the factors required for autonomous decision-making in mobility, positional awareness of the vehicle itself is the most critical. Accordingly, extensive research has been...

[SECURITY] Fedora 42 Update: brotli-1.2.0-1.fc42

Brotli is a generic-purpose lossless compression algorithm that compresses da ta using a combination of a modern variant of the LZ77 algorithm, Huffman coding and 2nd order context modeling, with a compression ratio comparable to the be st currently available general-purpose compression methods. ...

An Empirical Analysis of Zero-Day Vulnerabilities Disclosed by the Zero Day Initiative

Zero-day vulnerabilities represent some of the most critical threats in cybersecurity, as they correspond to previously unknown flaws in software or hardware that are actively exploited before vendors can develop and deploy patches. During this exposure window, affected systems remain defenseless...

A Practical Framework for Evaluating Medical AI Security: Reproducible Assessment of Jailbreaking and Privacy Vulnerabilities across Clinical Specialties

Medical Large Language Models LLMs are increasingly deployed for clinical decision support across diverse specialties, yet systematic evaluation of their robustness to adversarial misuse and privacy leakage remains inaccessible to most researchers. Existing security benchmarks require GPU cluster...

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features

Phishing is a cybercrime in which individuals are deceived into revealing personal information, often resulting in financial loss. These attacks commonly occur through fraudulent messages, misleading advertisements, and compromised legitimate websites. This study proposes a Quantile Regression De...

ASTRIDE: A Security Threat Modeling Platform for Agentic-AI Applications

AI agent-based systems are becoming increasingly integral to modern software architectures, enabling autonomous decision-making, dynamic task execution, and multimodal interactions through large language models LLMs. However, these systems introduce novel and evolving security challenges, includi...

Future-Back Threat Modeling: A Foresight-Driven Security Framework

Traditional threat modeling remains reactive-focused on known TTPs and past incident data, while threat prediction and forecasting frameworks are often disconnected from operational or architectural artifacts. This creates a fundamental weakness: the most serious cyber threats often do not arise...

Human-Centered Threat Modeling in Practice: Lessons, Challenges, and Paths Forward

Human-centered threat modeling HCTM is an emerging area within security and privacy research that focuses on how people define and navigate threats in various social, cultural, and technological contexts. While researchers increasingly approach threat modeling from a human-centered perspective,...

Threat Landscape of the Building and Construction Sector, Part One: Initial Access, Supply Chain, and the Internet of Things

In 2025, the construction industry stands at the crossroads of digital transformation and evolving cybersecurity risks, making it a prime target for threat actors. Cyber adversaries, including ransomware operators, organized cybercriminal networks, and state-sponsored APT groups from countries su...