Incorporating Taxonomies of Cyber Incidents into Detection Networks for Improved Detection Performance

Many taxonomies exist to organize cybercrime incidents into ontological categories. We examine some of the taxonomies introduced in the literature; providing a framework, and analysis, of how best to leverage different taxonomy structures to optimize performance of detections targeting various...

Extending the OWASP Multi-Agentic System Threat Modeling Guide: Insights from Multi-Agent Security Research

We propose an extension to the OWASP Multi-Agentic System MAS Threat Modeling Guide, translating recent anticipatory research in multi-agent security MASEC into practical guidance for addressing challenges unique to large language model LLM-driven multi-agent architectures. Although OWASP's...

CISA: Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators

This guidance outlines a process for OT owners and operators to create an asset inventory and OT taxonomy. This process includes defining scope and objectives for the inventory, identifying assets, collecting attributes, creating a taxonomy, managing data, and implementing asset life cycle...

Amazon Nova AI Challenge -- Trusted AI: Advancing Secure, AI-Assisted Software Development

AI systems for software development are rapidly gaining prominence, yet significant challenges remain in ensuring their safety. To address this, Amazon launched the Trusted AI track of the Amazon Nova AI Challenge, a global competition among 10 university teams to drive advances in secure AI. In...

Explainable Ensemble Learning for Graph-Based Malware Detection

Malware detection in modern computing environments demands models that are not only accurate but also interpretable and robust to evasive techniques. Graph neural networks GNNs have shown promise in this domain by modeling rich structural dependencies in graph-based program representations such a...

Can AI Keep a Secret? Contextual Integrity Verification: a Provable Security Architecture for LLMs

Large language models LLMs remain acutely vulnerable to prompt injection and related jailbreak attacks; heuristic guardrails rules, filters, LLM judges are routinely bypassed. We present Contextual Integrity Verification CIV, an inference-time security architecture that attaches cryptographically...

Shadow in the Cache: Unveiling and Mitigating Privacy Risks of KV-Cache in LLM Inference

The Key-Value KV cache, which stores intermediate attention computations Key and Value pairs to avoid redundant calculations, is a fundamental mechanism for accelerating Large Language Model LLM inference. However, this efficiency optimization introduces significant yet underexplored privacy risk...

Generalized Kennedy Receivers Enhanced CV-QKD in Turbulent Channels for Endogenous Security of Space-Air-Ground Integrated Network

Endogenous security in next-generation wireless communication systems attracts increasing attentions in recent years. A typical solution to endogenous security problems is the quantum key distribution QKD, where unconditional security can be achieved thanks to the inherent properties of quantum...

Securing Educational LLMs: a Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessment

Due to perceptions of efficiency and significant productivity gains, various organisations, including in education, are adopting Large Language Models LLMs into their workflows. Educator-facing, learner-facing, and institution-facing LLMs, collectively, Educational Large Language Models eLLMs,...

Exploring Cross-Stage Adversarial Transferability in Class-Incremental Continual Learning

Class-incremental continual learning addresses catastrophic forgetting by enabling classification models to preserve knowledge of previously learned classes while acquiring new ones. However, the vulnerability of the models against adversarial attacks during this process has not been investigated...

Surpassing the PLOB Bound in Continuous-Variable Quantum Secret Sharing Using a State-Discrimination Detector

Continuous-variable quantum secret sharing CVQSS is a promising approach to ensuring multi-party information security. While CVQSS offers practical ease of implementation, its present performance remains limited. In this paper, we propose a novel CVQSS protocol integrated with a...

Hypervisor-Based Double Extortion Ransomware Detection Method Using Kitsune Network Features

Double extortion ransomware attacks have become mainstream since many organizations adopt more robust and resilient data backup strategies against conventional crypto-ransomware. This paper presents detailed attack stages, tactics, procedures, and tools used in the double extortion ransomware...

Microsoft PlayReady Activation Protocol Issues

This advisory builds on prior disclosed work in 2022 regarding Microsoft PlayReady protocol issues that can lead to leaf certificate generation using fake identities...

IAG: Input-Aware Backdoor Attack on VLMs for Visual Grounding

Vision-language models VLMs have shown significant advancements in tasks such as visual grounding, where they localize specific objects in images based on natural language queries and images. However, security issues in visual grounding tasks for VLMs remain underexplored, especially in the conte...

MADPromptS: Unlocking Zero-Shot Morphing Attack Detection with Multiple Prompt Aggregation

Face Morphing Attack Detection MAD is a critical challenge in face recognition security, where attackers can fool systems by interpolating the identity information of two or more individuals into a single face image, resulting in samples that can be verified as belonging to multiple identities by...

Omnissa Secure Email Gateway / Unified Access Gateway SSRF

Omnissa Secure Email Gateway On-Premise SEG and Omnissa Unified Access Gateway On-Premise UAG suffer from a server-side request forgery vulnerability...

Load-Altering Attacks against Power Grids: a Case Study Using the GB-36 Bus System Open Dataset

The growing digitalization and the rapid adoption of high-powered Internet-of-Things IoT-enabled devices e.g., EV charging stations have increased the vulnerability of power grids to cyber threats. In particular, the so-called Load Altering Attacks LAAs can trigger rapid frequency fluctuations an...

Kigen eUICC Type Confusion

Security Explorations has further examined the security of Kigen eUICC cards with GSMA consumer certificates installed. This advisory is an update and expansion to the original research disclosed, however it does not disclose exact details. They do, however, state that the new issue seems more...

Secure Authentication Via Quantum Physical Unclonable Functions: a Review

Quantum Physical Unclonable Functions QPUFs offer a physically grounded approach to secure authentication, extending the capabilities of classical PUFs. This review covers their theoretical foundations and key implementation challenges - such as quantum memories and Haar-randomness -, and...

Developing a Transferable Federated Network Intrusion Detection System

Intrusion Detection Systems IDS are a vital part of a network-connected device. In this paper, we develop a deep learning based intrusion detection system that is deployed in a distributed setup across devices connected to a network. Our aim is to better equip deep learning models against unknown...

Enhance the Machine Learning Algorithm Performance in Phishing Detection with Keyword Features

Recently, we can observe a significant increase of the phishing attacks in the Internet. In a typical phishing attack, the attacker sets up a malicious website that looks similar to the legitimate website in order to obtain the end-users' information. This may cause the leakage of the sensitive...

Image Selective Encryption Analysis Using Mutual Information in CNN Based Embedding Space

As digital data transmission continues to scale, concerns about privacy grow increasingly urgent - yet privacy remains a socially constructed and ambiguously defined concept, lacking a universally accepted quantitative measure. This work examines information leakage in image data, a domain where...

Security Analysis of ChatGPT: Threats and Privacy Risks

As artificial intelligence technology continues to advance, chatbots are becoming increasingly powerful. Among them, ChatGPT, launched by OpenAI, has garnered widespread attention globally due to its powerful natural language processing capabilities based on the GPT model, which enables it to...

Evasive Ransomware Attacks Using Low-Level Behavioral Adversarial Examples

Protecting state-of-the-art AI-based cybersecurity defense systems from cyber attacks is crucial. Attackers create adversarial examples by adding small changes i.e., perturbations to the attack features to evade or fool the deep learning model. This paper introduces the concept of low-level...

Attacks and Defenses against LLM Fingerprinting

As large language models are increasingly deployed in sensitive environments, fingerprinting attacks pose significant privacy and security risks. We present a study of LLM fingerprinting from both offensive and defensive perspectives. Our attack methodology uses reinforcement learning to...

Deep Learning Models for Robust Facial Liveness Detection

In the rapidly evolving landscape of digital security, biometric authentication systems, particularly facial recognition, have emerged as integral components of various security protocols. However, the reliability of these systems is compromised by sophisticated spoofing attacks, where imposters...

FetFIDS: a Feature Embedding Attention Based Federated Network Intrusion Detection Algorithm

Intrusion Detection Systems IDS have an increasingly important role in preventing exploitation of network vulnerabilities by malicious actors. Recent deep learning based developments have resulted in significant improvements in the performance of IDS systems. In this paper, we present FetFIDS,...

Never Compromise to Vulnerabilities: a Comprehensive Survey on AI Governance

The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, that pose significant societal risks, including misinformation, inequity, security breaches, physical harm, and eroded...

Omnissa Workspace ONE UEM Path Traversal / Server-Side Request Forgery

Omnissa Workspace ONE UEM suffers from path traversal and server-side request forgery vulnerabilities...

EntraGoat - a Deliberately Vulnerable Entra ID Environment

EntraGoat is a deliberately vulnerable Microsoft Entra ID infrastructure designed to simulate real-world identity security misconfigurations and attack vectors. EntraGoat introduces intentional vulnerabilities in your environment to provide a realistic learning platform for security professionals...

Obfuscated Quantum and Post-Quantum Cryptography

In this work, we present an experimental deployment of a new design for combined quantum key distribution QKD and post-quantum cryptography PQC. Novel to our system is the dynamic obfuscation of the QKD-PQC sequence of operations, the number of operations, and parameters related to the operations...

Designing with Deception: ML- and Covert Gate-Enhanced Camouflaging to Thwart IC Reverse Engineering

Integrated circuits ICs are essential to modern electronic systems, yet they face significant risks from physical reverse engineering RE attacks that compromise intellectual property IP and overall system security. While IC camouflage techniques have emerged to mitigate these risks, existing...

AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders

As the social implementation of AI has been steadily progressing, research and development related to AI security has also been increasing. However, existing studies have been limited to organizing related techniques, attacks, defenses, and risks in terms of specific domains or AI elements. Thus,...

Chimera: Harnessing Multi-Agent LLMs for Automatic Insider Threat Simulation

Insider threats, which can lead to severe losses, remain a major security concern. While machine learning-based insider threat detection ITD methods have shown promising results, their progress is hindered by the scarcity of high-quality data. Enterprise data is sensitive and rarely accessible,...

BlindGuard: Safeguarding LLM-Based Multi-Agent Systems under Unknown Attacks

The security of LLM-based multi-agent systems MAS is critically threatened by propagation vulnerability, where malicious agents can distort collective decision-making through inter-agent message interactions. While existing supervised defense methods demonstrate promising performance, they may be...

VeriPHY: Physical Layer Signal Authentication for Wireless Communication in 5G Environments

Physical layer authentication PLA uses inherent characteristics of the communication medium to provide secure and efficient authentication in wireless networks, bypassing the need for traditional cryptographic methods. With advancements in deep learning, PLA has become a widely adopted technique...

Securing Agentic AI: Threat Modeling and Risk Analysis for Network Monitoring Agentic AI System

When combining Large Language Models LLMs with autonomous agents, used in network monitoring and decision-making systems, this will create serious security issues. In this research, the MAESTRO framework consisting of the seven layers threat modeling architecture in the system was used to expose,...

A Comparative Analysis of Lightweight Hash Functions Using AVR ATXMega128 and ChipWhisperer

Lightweight hash functions have become important building blocks for security in embedded and IoT systems. A plethora of algorithms have been proposed and standardized, providing a wide range of performance trade-off options for developers to choose from. This paper presents a comparative analysi...

Robust Anomaly Detection in O-RAN: Leveraging LLMs against Data Manipulation Attacks

The introduction of 5G and the Open Radio Access Network O-RAN architecture has enabled more flexible and intelligent network deployments. However, the increased complexity and openness of these architectures also introduce novel security challenges, such as data manipulation attacks on the...

Power Pwn 4.0.1

Power Pwn is a powerful open‑source toolset designed for red‑teaming and security testing within the Microsoft 365 environment, particularly around Copilot, Copilot Studio, and the Power Platform...

Generative AI for Cybersecurity of Energy Management Systems: Methods, Challenges, and Future Directions

This paper elaborates on an extensive security framework specifically designed for energy management systems EMSs, which effectively tackles the dynamic environment of cybersecurity vulnerabilities and/or system problems SPs, accomplished through the incorporation of novel methodologies. A...

VOIDFace: a Privacy-Preserving Multi-Network Face Recognition with Enhanced Security

Advancement of machine learning techniques, combined with the availability of large-scale datasets, has significantly improved the accuracy and efficiency of facial recognition. Modern facial recognition systems are trained using large face datasets collected from diverse individuals or public...

False Reality: Uncovering Sensor-Induced Human-VR Interaction Vulnerability

Virtual Reality VR techniques, serving as the bridge between the real and virtual worlds, have boomed and are widely used in manufacturing, remote healthcare, gaming, etc. Specifically, VR systems offer users immersive experiences that include both perceptions and actions. Various studies have...

Differential Privacy for Regulatory Compliance in Cyberattack Detection on Critical Infrastructure Systems

Industrial control systems are a fundamental component of critical infrastructure networks CIN such as gas, water and power. With the growing risk of cyberattacks, regulatory compliance requirements are also increasing for large scale critical infrastructure systems comprising multiple utility...

Generative AI for Critical Infrastructure in Smart Grids: a Unified Framework for Synthetic Data Generation and Anomaly Detection

In digital substations, security events pose significant challenges to the sustained operation of power systems. To mitigate these challenges, the implementation of robust defense strategies is critically important. A thorough process of anomaly identification and detection in information and...

Belkin F9K1009 / F9K1010 Authentication Bypass

This repository contains a exploit for CVE‑2025‑8730, a critical Authentication Bypass vulnerability affecting the web interface of Belkin F9K1009 and F9K1010 routers. The flaw lies in the session validation logic of the /login.htm file, where improperly handled cookies or crafted requests allow...

Selective KV-Cache Sharing to Mitigate Timing Side-Channels in LLM Inference

Global KV-cache sharing has emerged as a key optimization for accelerating large language model LLM inference. However, it exposes a new class of timing side-channel attacks, enabling adversaries to infer sensitive user inputs via shared cache entries. Existing defenses, such as per-user isolatio...

Jetty 10.0.6 HTTP/2 Stream Exhaustion Denial of Service

Jetty version 10.0.6 is vulnerable to a denial of service condition via HTTP/2 stream exhaustion. By opening and maintaining a large number of idle HTTP/2 streams, an attacker can exhaust server resources and cause the service to become unresponsive. This archive includes a Ruby Metasploit...

TraceLens: Question-Driven Debugging for Taint Flow Understanding

Taint analysis is a security analysis technique used to track the flow of potentially dangerous data through an application and its dependent libraries. Investigating why certain unexpected flows appear and why expected flows are missing is an important sensemaking process during end-user taint...

Civil Servants As Builders: Enabling Non-IT Staff to Develop Secure Python and R Tools

Current digital government literature focuses on professional in-house IT teams, specialized digital service teams, vendor-developed systems, or proprietary low-code/no-code tools. Almost no scholarship addresses a growing middle ground: technically skilled civil servants outside formal IT roles...