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...

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...

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

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

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...

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,...

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...

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,...

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,...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

Certifiably Robust Malware Detectors by Design

Malware analysis involves analyzing suspicious software to detect malicious payloads. Static malware analysis, which does not require software execution, relies increasingly on machine learning techniques to achieve scalability. Although such techniques obtain very high detection accuracy, they c...

Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information...

Enhancing Privacy in Decentralized Min-Max Optimization: a Differentially Private Approach

Decentralized min-max optimization allows multi-agent systems to collaboratively solve global min-max optimization problems by facilitating the exchange of model updates among neighboring agents, eliminating the need for a central server. However, sharing model updates in such systems carry a ris...

Cognitive Cybersecurity for Artificial Intelligence: Guardrail Engineering with CCS-7

Language models exhibit human-like cognitive vulnerabilities, such as emotional framing, that escape traditional behavioral alignment. We present CCS-7 Cognitive Cybersecurity Suite, a taxonomy of seven vulnerabilities grounded in human cognitive security research. To establish a human benchmark,...

Neural Network-Based Detection and Multi-Class Classification of FDI Attacks in Smart Grid Home Energy Systems

False Data Injection Attacks FDIAs pose a significant threat to smart grid infrastructures, particularly Home Area Networks HANs, where real-time monitoring and control are highly adopted. Owing to the comparatively less stringent security controls and widespread availability of HANs, attackers...

Balancing Privacy and Efficiency: Music Information Retrieval Via Additive Homomorphic Encryption

In the era of generative AI, ensuring the privacy of music data presents unique challenges: unlike static artworks such as images, music data is inherently temporal and multimodal, and it is sampled, transformed, and remixed at an unprecedented scale. These characteristics make its core vector...

Who'S the Evil Twin? Differential Auditing for Undesired Behavior

Detecting hidden behaviors in neural networks poses a significant challenge due to minimal prior knowledge and potential adversarial obfuscation. We explore this problem by framing detection as an adversarial game between two teams: the red team trains two similar models, one trained solely on...

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection

Ensuring LLM alignment is critical to information security as AI models become increasingly widespread and integrated in society. Unfortunately, many defenses against adversarial attacks and jailbreaking on LLMs cannot adapt quickly to new attacks, degrade model responses to benign prompts, or...

Symbolic Execution in Practice: a Survey of Applications in Vulnerability, Malware, Firmware, and Protocol Analysis

Symbolic execution is a powerful program analysis technique that allows for the systematic exploration of all program paths. Path explosion, where the number of states to track becomes unwieldy, is one of the biggest challenges hindering symbolic execution's practical application. To combat this,...

MALRIS: Malicious Hardware in RIS-Assisted Wireless Communications

Reconfigurable intelligent surfaces RIS enhance wireless communication by dynamically shaping the propagation environment, but their integration introduces hardware-level security risks. This paper presents the concept of Malicious RIS MALRIS, where compromised components behave adversarially, ev...

EU Digital Regulation and Guatemala: AI, 5G, and Cybersecurity

The paper examines how EU rules in AI, 5G, and cybersecurity operate as transnational governance and shape policy in Guatemala. It outlines the AI Act's risk approach, the 5G Action Plan and Security Toolbox, and the cybersecurity regime built on ENISA, NIS2, the Cybersecurity Act, and the Cyber...

Latent Fusion Jailbreak: Blending Harmful and Harmless Representations to Elicit Unsafe LLM Outputs

Large language models LLMs demonstrate impressive capabilities in various language tasks but are susceptible to jailbreak attacks that circumvent their safety alignments. This paper introduces Latent Fusion Jailbreak LFJ, a representation-based attack that interpolates hidden states from harmful...

Confluence Broken Access Control

This script is designed to exploit the CVE-2023-22515 vulnerability in Confluence, which allows for unauthorized access to Confluence Server and Confluence Data Center instances. The vulnerability is categorized as a broken access control issue and has a CVSS base score of 10.0...

Label Inference Attacks against Federated Unlearning

Federated Unlearning FU has emerged as a promising solution to respond to the right to be forgotten of clients, by allowing clients to erase their data from global models without compromising model performance. Unfortunately, researchers find that the parameter variations of models induced by FU...

ScamAgents: How AI Agents Can Simulate Human-Level Scam Calls

Large Language Models LLMs have demonstrated impressive fluency and reasoning capabilities, but their potential for misuse has raised growing concern. In this paper, we present ScamAgent, an autonomous multi-turn agent built on top of LLMs, capable of generating highly realistic scam call scripts...

Beyond Uniform Criteria: Scenario-Adaptive Multi-Dimensional Jailbreak Evaluation

Precise jailbreak evaluation is vital for LLM red teaming and jailbreak research. Current approaches employ binary classification e.g., string matching, toxic text classifiers, LLM-driven methods, yielding only "yes/no" labels without quantifying harm intensity. Existing multi-dimensional...

WordPress Bricks 1.9.6 Remote Code Execution

This tool is designed to exploit the CVE-2024-25600 vulnerability found in the Bricks Builder plugin for WordPress versions 1.9.6 and below. The vulnerability allows for unauthenticated remote code execution on affected websites. The tool automates the exploitation process by retrieving nonces an...

ProvX: Generating Counterfactual-Driven Attack Explanations for Provenance-Based Detection

Provenance graph-based intrusion detection systems are deployed on hosts to defend against increasingly severe Advanced Persistent Threat. Using Graph Neural Networks to detect these threats has become a research focus and has demonstrated exceptional performance. However, the widespread adoption...

Microsoft SharePoint Privilege Escalation

This script exploits a vulnerability in Microsoft SharePoint Server allowing remote attackers to escalate privileges on affected installations. While this script focuses on elevation of privilege, attackers with malicious intent might chain this vulnerability with a remote code execution...

Topology Generation of UAV Covert Communication Networks: a Graph Diffusion Approach with Incentive Mechanism

With the growing demand for Uncrewed Aerial Vehicle UAV networks in sensitive applications, such as urban monitoring, emergency response, and secure sensing, ensuring reliable connectivity and covert communication has become increasingly vital. However, dynamic mobility and exposure risks pose...

CitrixBleed 2 Mass Scanner

This script is a mass scanner for the CitrixBleed 2 vulnerability...

Membership Inference Attack with Partial Features

Machine learning models have been shown to be susceptible to membership inference attack, which can be used to determine whether a given sample appears in the training data. Existing membership inference methods commonly assume that the adversary has full access to the features of the target...

Mitigating Distribution Shift in Graph-Based Android Malware Classification Via Function Metadata and LLM Embeddings

Graph-based malware classifiers can achieve over 94% accuracy on standard Android datasets, yet we find they suffer accuracy drops of up to 45% when evaluated on previously unseen malware variants from the same family - a scenario where strong generalization would typically be expected. This...

Simulation in Cybersecurity: Understanding Techniques, Applications, and Goals

Modeling and simulation are widely used in cybersecurity research to assess cyber threats, evaluate defense mechanisms, and analyze vulnerabilities. However, the diversity of application areas, the variety of cyberattacks scenarios, and the differing objectives of these simulations makes it...

Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models: a Unified and Accurate Approach

Despite extensive alignment efforts, Large Vision-Language Models LVLMs remain vulnerable to jailbreak attacks, posing serious safety risks. Although recent detection works have shifted to internal representations due to their rich cross-modal information, most methods rely on heuristic rules...