1329 matches found
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...
SoK: Taxonomy and Evaluation of Prompt Security in Large Language Models
Large Language Models LLMs have rapidly become integral to real-world applications, powering services across diverse sectors. However, their widespread deployment has exposed critical security risks, particularly through jailbreak prompts that can bypass model alignment and induce harmful outputs...
TITAN: Graph-Executable Reasoning for Cyber Threat Intelligence
TITAN Threat Intelligence Through Automated Navigation is a framework that connects natural-language cyber threat queries with executable reasoning over a structured knowledge graph. It integrates a path planner model, which predicts logical relation chains from text, and a graph executor that...
Lightweight CNN-Based Wi-Fi Intrusion Detection Using 2D Traffic Representations
Wi-Fi networks are ubiquitous in both home and enterprise environments, serving as a primary medium for Internet access and forming the backbone of modern IoT ecosystems. However, their inherent vulnerabilities, combined with widespread adoption, create opportunities for malicious actors to gain...
completedPoCs
Enhanced PoC Dataset for Security Research This repository hos...
EUVD-2021-13492
Malware in sbrugna...
EUVD-2013-5262
Malware in sbrugna...
EUVD-2019-0441
Malware in sbrugna...
MulVuln: Enhancing Pre-Trained LMs with Shared and Language-Specific Knowledge for Multilingual Vulnerability Detection
Software vulnerabilities SVs pose a critical threat to safety-critical systems, driving the adoption of AI-based approaches such as machine learning and deep learning for software vulnerability detection. Despite promising results, most existing methods are limited to a single programming languag...
EUVD-2023-34943
Malicious code in bioql PyPI...
EUVD-2023-26945
Malicious code in bioql PyPI...
EUVD-2023-3144
Malicious code in bioql PyPI...