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...

Temporal Analysis Framework for Intrusion Detection Systems: A Novel Taxonomy for Time-Aware Cybersecurity

Most intrusion detection systems still identify attacks only after significant damage has occurred, detecting late-stage tactics rather than early indicators of compromise. This paper introduces a temporal analysis framework and taxonomy for time-aware network intrusion detection. Through a...

AgentCyTE: Leveraging Agentic AI to Generate Cybersecurity Training and Experimentation Scenarios

Designing realistic and adaptive networked threat scenarios remains a core challenge in cybersecurity research and training, still requiring substantial manual effort. While large language models LLMs show promise for automated synthesis, unconstrained generation often yields configurations that...

AAGATE: A NIST AI RMF-Aligned Governance Platform for Agentic AI

This paper introduces the Agentic AI Governance Assurance & Trust Engine AAGATE, a Kubernetes-native control plane designed to address the unique security and governance challenges posed by autonomous, language-model-driven agents in production. Recognizing the limitations of traditional...

appsec-sentinel

AppSec-Sentinel AI-powered security scanner with cross-file...

Advancing Honeywords for Real-World Authentication Security

Introduced by Juels and Rivest in 2013, Honeywords, which are decoy passwords stored alongside a real password, appear to be a proactive method to help detect password credentials misuse. However, despite over a decade of research, this technique has not been adopted by major authentication...

Intermittent File Encryption in Ransomware: Measurement, Modeling, and Detection

File encrypting ransomware increasingly employs intermittent encryption techniques, encrypting only parts of files to evade classical detection methods. These strategies, exemplified by ransomware families like BlackCat, complicate file structure based detection techniques due to diverse file...