Sustaining Cyber Awareness: The Long-Term Impact of Continuous Phishing Training and Emotional Triggers

Phishing constitutes more than 90% of successful cyberattacks globally, remaining one of the most persistent threats to organizational security. Despite organizations tripling their cybersecurity budgets between 2015 and 2025, the human factor continues to pose a critical vulnerability. This stud...

Coordinated Position Falsification Attacks and Countermeasures for Location-Based Services

With the rise of location-based service LBS applications that rely on terrestrial and satellite infrastructures e.g., GNSS and crowd-sourced Wi-Fi, Bluetooth, cellular, and IP databases for positioning, ensuring their integrity and security is paramount. However, we demonstrate that these...

Exploiting Latent Space Discontinuities for Building Universal LLM Jailbreaks and Data Extraction Attacks

The rapid proliferation of Large Language Models LLMs has raised significant concerns about their security against adversarial attacks. In this work, we propose a novel approach to crafting universal jailbreaks and data extraction attacks by exploiting latent space discontinuities, an architectur...

On Selecting Few-Shot Examples for LLM-Based Code Vulnerability Detection

Large language models LLMs have demonstrated impressive capabilities for many coding tasks, including summarization, translation, completion, and code generation. However, detecting code vulnerabilities remains a challenging task for LLMs. An effective way to improve LLM performance is in-context...

Mind the Gap: Missing Cyber Threat Coverage in NIDS Datasets for the Energy Sector

Network Intrusion Detection Systems NIDS developed using publicly available datasets predominantly focus on enterprise environments, raising concerns about their effectiveness for converged Information Technology IT and Operational Technology OT in energy infrastructures. This study evaluates the...

Prevalence of Security and Privacy Risk-Inducing Usage of AI-Based Conversational Agents

Recent improvement gains in large language models LLMs have lead to everyday usage of AI-based Conversational Agents CAs. At the same time, LLMs are vulnerable to an array of threats, including jailbreaks and, for example, causing remote code execution when fed specific inputs. As a result, users...

Service Upstart Persistence

This Metasploit module will create a service on the box, and mark it for auto-restart. You need enough access to write service files and potentially restart services...

MH-1M: A 1.34 Million-Sample Comprehensive Multi-Feature Android Malware Dataset for Machine Learning, Deep Learning, Large Language Models, and Threat Intelligence Research

We present MH-1M, one of the most comprehensive and up-to-date datasets for advanced Android malware research. The dataset comprises 1,340,515 applications, encompassing a wide range of features and extensive metadata. To ensure accurate malware classification, we employ the VirusTotal API,...

MalDataGen: A Modular Framework for Synthetic Tabular Data Generation in Malware Detection

High-quality data scarcity hinders malware detection, limiting ML performance. We introduce MalDataGen, an open-source modular framework for generating high-fidelity synthetic tabular data using modular deep learning models e.g., WGAN-GP, VQ-VAE. Evaluated via dual validation TR-TS/TS-TR, seven...

Adapting Large Language Models to Emerging Cybersecurity Using Retrieval Augmented Generation

Security applications are increasingly relying on large language models LLMs for cyber threat detection; however, their opaque reasoning often limits trust, particularly in decisions that require domain-specific cybersecurity knowledge. Because security threats evolve rapidly, LLMs must not only...

Unvalidated Trust: Cross-Stage Vulnerabilities in Large Language Model Architectures

As Large Language Models LLMs are increasingly integrated into automated, multi-stage pipelines, risk patterns that arise from unvalidated trust between processing stages become a practical concern. This paper presents a mechanism-centered taxonomy of 41 recurring risk patterns in commercial LLMs...

A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection

Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essential for ensuring system resilience. Graph-based approaches have become increasingly important for modeling entity interactions, yet most rely on homogeneou...

CyberNER: A Harmonized STIX Corpus for Cybersecurity Named Entity Recognition

Extracting structured intelligence via Named Entity Recognition NER is critical for cybersecurity, but the proliferation of datasets with incompatible annotation schemas hinders the development of comprehensive models. While combining these resources is desirable, we empirically demonstrate that...

TEE.fail: Breaking Trusted Execution Environments via DDR5 Memory Bus Interposition

In this paper, the researchers show that the security guarantees of modern TEE offerings by Intel and AMD can be broken cheaply and easily, by building a memory interposition device that allows attackers to physically inspect all memory traffic inside a DDR5 server...

A Comparative Study of Hybrid Post-Quantum Cryptographic X.509 Certificate Schemes

As quantum computing hardware continues to advance, the integration of such technology with quantum algorithms is anticipated to enable the decryption of ciphertexts produced by RSA and Elliptic Curve Cryptography ECC within polynomial time. In response to this emerging threat, the U.S. National...

LLM-Based Multi-Class Attack Analysis and Mitigation Framework in IoT/IIoT Networks

The Internet of Things has expanded rapidly, transforming communication and operations across industries but also increasing the attack surface and security breaches. Artificial Intelligence plays a key role in securing IoT, enabling attack detection, attack behavior analysis, and mitigation...

A DRL-Empowered Multi-Level Jamming Approach for Secure Semantic Communication

Semantic communication SemCom aims to transmit only task-relevant information, thereby improving communication efficiency but also exposing semantic information to potential eavesdropping. In this paper, we propose a deep reinforcement learning DRL-empowered multi-level jamming approach to enhanc...

A Comprehensive Evaluation and Practice of System Penetration Testing

With the rapid advancement of information technology, the complexity of applications continues to increase, and the cybersecurity challenges we face are also escalating. This paper aims to investigate the methods and practices of system security penetration testing, exploring how to enhance syste...

Twin-Field Quantum Key Distribution: Protocols, Security, and Open Problems

Twin-Field Quantum Key Distribution TF-QKD has emerged as a potential protocol for long distance secure communication, overcoming the rate-distance limitations of conventional quantum key distribution without requiring trusted repeaters. By having two parties transmit phase encoded weak coherent...

tc Tor Chat Client 1.3

tc is a low-tech free solution to make yourself anonymously reachable for chat by anyone who only know your onion address and your public key. Messages are PGP encrypted end-to-end and forwarded by Tor's relays...

Windows Persistent Startup Folder

This Metasploit module establishes persistence by creating a payload in the user or system startup folder. Works on Vista and newer systems...

SIRAJ: Diverse and Efficient Red-Teaming for LLM Agents Via Distilled Structured Reasoning

The ability of LLM agents to plan and invoke tools exposes them to new safety risks, making a comprehensive red-teaming system crucial for discovering vulnerabilities and ensuring their safe deployment. We present SIRAJ: a generic red-teaming framework for arbitrary black-box LLM agents. We emplo...

Model Inversion Attacks Meet Cryptographic Fuzzy Extractors

Model inversion attacks pose an open challenge to privacy-sensitive applications that use machine learning ML models. For example, face authentication systems use modern ML models to compute embedding vectors from face images of the enrolled users and store them. If leaked, inversion attacks can...

Security Vulnerabilities in AI-Generated Code: A Large-Scale Analysis of Public GitHub Repositories

This paper presents a comprehensive empirical analysis of security vulnerabilities in AI-generated code across public GitHub repositories. We collected and analyzed 7,703 files explicitly attributed to four major AI tools: ChatGPT 91.52%, GitHub Copilot 7.50%, Amazon CodeWhisperer 0.52%, and...

Packet Fence 15.0.0

PacketFence is a network access control NAC system. It is actively maintained and has been deployed in numerous large-scale institutions. It can be used to effectively secure networks, from small to very large heterogeneous networks. PacketFence provides NAC-oriented features such as registration...

Identity Management for Agentic AI: The New Frontier of Authorization, Authentication, and Security for an AI Agent World

The rapid rise of AI agents presents urgent challenges in authentication, authorization, and identity management. Current agent-centric protocols like MCP highlight the demand for clarified best practices in authentication and authorization. Looking ahead, ambitions for highly autonomous agents...

An In-Depth Analysis of Cyber Attacks in Secured Platforms

There is an increase in global malware threats. To address this, an encryption-type ransomware has been introduced on the Android operating system. The challenges associated with malicious threats in phone use have become a pressing issue in mobile communication, disrupting user experiences and...

APThreatHunter: An Automated Planning-Based Threat Hunting Framework

Cyber attacks threaten economic interests, critical infrastructure, and public health and safety. To counter this, entities adopt cyber threat hunting, a proactive approach that involves formulating hypotheses and searching for attack patterns within organisational networks. Automating cyber thre...

Is Protective DNS Blocking the Wild West?

We perform a passive measurement study investigating how a Protective DNS service might perform in a Research & Education Network serving hundreds of member institutions. Utilizing freely-available DNS blocklists consisting of domain names deemed to be threats, we test hundreds of millions of...

From ECU to VSOC: UDS Security Monitoring Strategies

Increasing complexity and connectivity of modern vehicles have heightened their vulnerability to cyberattacks. This paper addresses security challenges associated with the Unified Diagnostic Services UDS protocol, a critical communication framework for vehicle diagnostics in the automotive...

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...

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...

Secure Retrieval-Augmented Generation against Poisoning Attacks

Large language models LLMs have transformed natural language processing NLP, enabling applications from content generation to decision support. Retrieval-Augmented Generation RAG improves LLMs by incorporating external knowledge but also introduces security risks, particularly from data poisoning...

Covert Surveillance in Smart Devices: A SCOUR Framework Analysis of Youth Privacy Implications

This paper investigates how smart devices covertly capture private conversations and discusses in more in-depth the implications of this for youth privacy. Using a structured review guided by the PRISMA methodology, the analysis focuses on privacy concerns, data capture methods, data storage and...

Hammering the Diagnosis: Rowhammer-Induced Stealthy Trojan Attacks on ViT-Based Medical Imaging

Vision Transformers ViTs have emerged as powerful architectures in medical image analysis, excelling in tasks such as disease detection, segmentation, and classification. However, their reliance on large, attention-driven models makes them vulnerable to hardware-level attacks. In this paper, we...

Attention Augmented GNN RNN-Attention Models for Advanced Cybersecurity Intrusion Detection

In this paper, we propose a novel hybrid deep learning architecture that synergistically combines Graph Neural Networks GNNs, Recurrent Neural Networks RNNs, and multi-head attention mechanisms to significantly enhance cybersecurity intrusion detection capabilities. By leveraging the comprehensiv...

Quantum-Resistant Networks Using Post-Quantum Cryptography

Quantum networks rely on both quantum and classical channels for coordinated operation. Current architectures employ entanglement distribution and key exchange over quantum channels but often assume that classical communication is sufficiently secure. In practice, classical channels protected by...

Wapiti Web Application Vulnerability Scanner 3.2.8

Wapiti is a web application vulnerability scanner. It will scan the web pages of a deployed web application and will fuzz the URL parameters and forms to find common web vulnerabilities. This is the binary release...

Network Intrusion Detection: Evolution from Conventional Approaches to LLM Collaboration and Emerging Risks

This survey systematizes the evolution of network intrusion detection systems NIDS, from conventional methods such as signature-based and neural network NN-based approaches to recent integrations with large language models LLMs. It clearly and concisely summarizes the current status, strengths, a...

MCPGuard : Automatically Detecting Vulnerabilities in MCP Servers

The Model Context Protocol MCP has emerged as a standardized interface enabling seamless integration between Large Language Models LLMs and external data sources and tools. While MCP significantly reduces development complexity and enhances agent capabilities, its openness and extensibility...

A Neuro-Symbolic Multi-Agent Approach to Legal-Cybersecurity Knowledge Integration

The growing intersection of cybersecurity and law creates a complex information space where traditional legal research tools struggle to deal with nuanced connections between cases, statutes, and technical vulnerabilities. This knowledge divide hinders collaboration between legal experts and...

QueryIPI: Query-Agnostic Indirect Prompt Injection on Coding Agents

Modern coding agents integrated into IDEs combine powerful tools and system-level actions, exposing a high-stakes attack surface. Existing Indirect Prompt Injection IPI studies focus mainly on query-specific behaviors, leading to unstable attacks with lower success rates. We identify a more sever...

Evaluation of Vision-LLMs in Surveillance Video

The widespread use of cameras in our society has created an overwhelming amount of video data, far exceeding the capacity for human monitoring. This presents a critical challenge for public safety and security, as the timely detection of anomalous or criminal events is crucial for effective...

Victim As a Service: Designing a System for Engaging with Interactive Scammers

Pig butchering, and similar interactive online scams, lower their victims' defenses by building trust over extended periods of conversation - sometimes weeks or months. They have become increasingly public losses at least $75B by one recent study. However, because of their long-term conversationa...

Secure Control of Connected and Autonomous Electrified Vehicles under Adversarial Cyber-Attacks

Connected and Autonomous Electrified Vehicles CAEV is the solution to the future smart mobility having benefits of efficient traffic flow and cleaner environmental impact. Although CAEV has advantages they are still susceptible to adversarial cyber attacks due to their autonomous electric operati...

Wapiti Web Application Vulnerability Scanner 3.2.8 Source Code

Wapiti is a web application vulnerability scanner. It will scan the web pages of a deployed web application and will fuzz the URL parameters and forms to find common web vulnerabilities. This is the source code release...

Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges

Agentic AI systems powered by large language models LLMs and endowed with planning, tool use, memory, and autonomy, are emerging as powerful, flexible platforms for automation. Their ability to autonomously execute tasks across web, software, and physical environments creates new and amplified...

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...

Is Your Prompt Poisoning Code? Defect Induction Rates and Security Mitigation Strategies

Large language models LLMs have become indispensable for automated code generation, yet the quality and security of their outputs remain a critical concern. Existing studies predominantly concentrate on adversarial attacks or inherent flaws within the models. However, a more prevalent yet...

RejSCore: Rejection Sampling Core for Multivariate-Based Public Key Cryptography

Post-quantum multivariate public key cryptography MPKC schemes resist quantum threats but require heavy operations, such as rejection sampling, which challenge resource-limited devices. Prior hardware designs have addressed various aspects of MPKC signature generation. However, rejection sampling...