1 PoCo: Agentic Proof-Of-Concept Exploit Generation for Smart Contracts

Smart contracts operate in a highly adversarial environment, where vulnerabilities can lead to substantial financial losses. Thus, smart contracts are subject to security audits. In auditing, proof-of-concept PoC exploits play a critical role by demonstrating to the stakeholders that the reported...

Federated Cyber Defense: Privacy-Preserving Ransomware Detection across Distributed Systems

Detecting malware, especially ransomware, is essential to securing today's interconnected ecosystems, including cloud storage, enterprise file-sharing, and database services. Training high-performing artificial intelligence AI detectors requires diverse datasets, which are often distributed acros...

Characterizing Build Compromises through Vulnerability Disclosure Analysis

The software build process transforms source code into deployable artifacts, representing a critical yet vulnerable stage in software development. Build infrastructure security poses unique challenges: the complexity of multi-component systems source code, dependencies, build tools, the difficult...

Android Malware Detection: A Machine Learning Approach

This study examines machine learning techniques like Decision Trees, Support Vector Machines, Logistic Regression, Neural Networks, and ensemble methods to detect Android malware. The study evaluates these models on a dataset of Android applications and analyzes their accuracy, efficiency, and...

A Large Scale Study of AI-Based Binary Function Similarity Detection Techniques for Security Researchers and Practitioners

Binary Function Similarity Detection BFSD is a foundational technique in software security, underpinning a wide range of applications including vulnerability detection, malware analysis. Recent advances in AI-based BFSD tools have led to significant performance improvements. However, existing...

Meta-Learning Based Radio Frequency Fingerprinting for GNSS Spoofing Detection

The rapid development of technology has led to an increase in the number of devices that rely on position, velocity, and time PVT information to perform their functions. As such, the Global Navigation Satellite Systems GNSS have been adopted as one of the most promising solutions to provide PVT...

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...

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,...

Cross-site Scripting (XSS)

Overview ckan is a world’s leading Open Source data portal platform. It powers dozens of Open Data portals around the world, including data.gov, open.canada.ca and europeandataportal.eu but also regional, research and community organizations. It makes easy to publish, share and find data online a...

EUVD-2025-36667

CKAN vulnerable to stored XSS in resource description...

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...

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...

Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents

AI agents powered by large language models LLMs are being deployed at scale, yet we lack a systematic understanding of how the choice of backbone LLM affects agent security. The non-deterministic sequential nature of AI agents complicates security modeling, while the integration of traditional...

Jailbreak Mimicry: Automated Discovery of Narrative-Based Jailbreaks for Large Language Models

Large language models LLMs remain vulnerable to sophisticated prompt engineering attacks that exploit contextual framing to bypass safety mechanisms, posing significant risks in cybersecurity applications. We introduce Jailbreak Mimicry, a systematic methodology for training compact attacker mode...

Quantum Autoencoders for Anomaly Detection in Cybersecurity

Anomaly detection in cybersecurity is a challenging task, where normal events far outnumber anomalous ones with new anomalies occurring frequently. Classical autoencoders have been used for anomaly detection, but struggles in data-limited settings which quantum counterparts can potentially...

Prompting the Priorities: A First Look at Evaluating LLMs for Vulnerability Triage and Prioritization

Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models LLMs offer a potential aid by automating parts of the interpretation process. We evaluate four models ChatGPT, Claude, Gemini, and DeepSeek across twelve prompting techniques to...

CLASP: Cost-Optimized LLM-Based Agentic System for Phishing Detection

Phishing websites remain a significant cybersecurity threat, necessitating accurate and cost-effective detection mechanisms. In this paper, we present CLASP, a novel system that effectively identifies phishing websites by leveraging multiple intelligent agents, built using large language models...

DataEase SQL Injection Vulnerability

DataEase is a set of Java-based development of open source data visualization and analysis tools to help users quickly analyze data and insight into business trends , so as to achieve business improvement and optimization . DataEase /de2api/datasetData/tableField processing tableName parameter...

ThreatIntel-Andro: Expert-Verified Benchmarking for Robust Android Malware Research

The rapidly evolving Android malware ecosystem demands high-quality, real-time datasets as a foundation for effective detection and defense. With the widespread adoption of mobile devices across industrial systems, they have become a critical yet often overlooked attack surface in industrial...

Toward Understanding Security Issues in the Model Context Protocol Ecosystem

The Model Context Protocol MCP is an emerging open standard that enables AI-powered applications to interact with external tools through structured metadata. A rapidly growing ecosystem has formed around MCP, including a wide range of MCP hosts i.e., Cursor, Windsurf, Claude Desktop, and Cline, M...