Related papers: Large Multimodal Agents for Accurate Phishing Dete…

Mobile advertising dominates app monetization but introduces risks ranging from intrusive user experience to malware delivery. Existing detection methods rely either on static analysis, which misses runtime behaviors, or on heuristic UI…

Phishing remains the most pervasive threat to the Web, enabling large-scale credential theft and financial fraud through deceptive webpages. While recent reference-based and generative-AI-driven phishing detectors achieve strong accuracy,…

The way we communicate and work has changed significantly with the rise of the Internet. While it has opened up new opportunities, it has also brought about an increase in cyber threats. One common and serious threat is phishing, where…

In this paper, we propose a feature-free method for detecting phishing websites using the Normalized Compression Distance (NCD), a parameter-free similarity measure which computes the similarity of two websites by compressing them, thus…

The persistent growth in phishing and the rising volume of phishing websites has led to individuals and organizations worldwide becoming increasingly exposed to various cyber-attacks. Consequently, more effective phishing detection is…

Web traffic has evolved to include both human users and automated agents, ranging from benign web crawlers to adversarial scanners such as those capable of credential stuffing, command injection, and account hijacking at the web scale. The…

Each month, more attacks are launched with the aim of making web users believe that they are communicating with a trusted entity which compels them to share their personal, financial information. Phishing costs Internet users billions of…

The increasing complexity of cyber threats in distributed environments demands advanced frameworks for real-time detection and response across multimodal data streams. This paper introduces AgenticCyber, a generative AI powered multi-agent…

In this digital era, our lives highly depend on the internet and worldwide technology. Wide usage of technology and platforms of communication makes our lives better and easier. But on the other side it carries out some security issues and…

Phishing attacks are one of the most common social engineering attacks targeting users emails to fraudulently steal confidential and sensitive information. They can be used as a part of more massive attacks launched to gain a foothold in…

Few-shot prompting has emerged as a practical alternative to fine-tuning for leveraging the capabilities of large language models (LLMs) in specialized tasks. However, its effectiveness depends heavily on the selection and quality of…

Large language models(LLMs) have demonstrated remarkable performance on many natural language processing(NLP) tasks and have been employed in phishing email detection research. However, in current studies, well-performing LLMs typically…

The widespread accessibility of the Internet has led to a surge in online fraudulent activities, underscoring the necessity of shielding users' sensitive information from cybercriminals. Phishing, a well-known cyberattack, revolves around…

Phishing webpages are continuously polluting the Web. Plenty of countermeasures have been proposed and the most advanced techniques leverage machine-learning methods that infer whether a webpage is benign or not by inspecting its visual…

Large Language Models (LLMs) excel in diverse applications including generation of code snippets, but often struggle with generating code for complex Machine Learning (ML) tasks. Although existing LLM single-agent based systems give varying…

Computer use agents create new privacy risks: training data collected from real websites inevitably contains sensitive information, and cloud-hosted inference exposes user screenshots. Detecting personally identifiable information in web…

Phishing is one of the most prolific cybercriminal activities, with attacks becoming increasingly sophisticated. It is, therefore, imperative to explore novel technologies to improve user protection across both technical and human…

Large Language Models (LLMs) have been a promising way for automated vulnerability detection. However, most prior studies have explored the use of LLMs to detect vulnerabilities only within single functions, disregarding those related to…

Automated bots now account for roughly half of all web requests, and an increasing number deliberately spoof their identity to either evade detection or to not respect robots.txt. Existing countermeasures are either resource-intensive…

Getting a real cybersecurity risk assessment for a small organization is expensive -- a NIST CSF-aligned engagement runs $15,000 on the low end, takes weeks, and depends on practitioners who are genuinely scarce. Most small companies skip…