Cover Image

PhishParrot: LLM-Driven Adaptive Crawling to Unveil Cloaked Phishing Sites

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nakano, Hiroki, Koide, Takashi, Chiba, Daiki
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PhishLumos: An Adaptive Multi-Agent System for Proactive Phishing Campaign Mitigation
by: Chiba, Daiki, et al.
Published: (2025)

Detecting Phishing Sites Using ChatGPT
by: Koide, Takashi, et al.
Published: (2023)

Clouding the Mirror: Stealthy Prompt Injection Attacks Targeting LLM-based Phishing Detection
by: Koide, Takashi, et al.
Published: (2026)

ChatSpamDetector: Leveraging Large Language Models for Effective Phishing Email Detection
by: Koide, Takashi, et al.
Published: (2024)

ScamFerret: Detecting Scam Websites Autonomously with Large Language Models
by: Nakano, Hiroki, et al.
Published: (2025)

DomainDynamics: Lifecycle-Aware Risk Timeline Construction for Domain Names
by: Chiba, Daiki, et al.
Published: (2024)

DomainLynx: Leveraging Large Language Models for Enhanced Domain Squatting Detection
by: Chiba, Daiki, et al.
Published: (2024)

DomainHarvester: Harvesting Infrequently Visited Yet Trustworthy Domain Names
by: Chiba, Daiki, et al.
Published: (2024)

PhishDebate: An LLM-Based Multi-Agent Framework for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

MultiPhishGuard: An Explainable and Adaptive Multi-Agent LLM System for Phishing Email Detection
by: Xue, Yinuo, et al.
Published: (2025)

The Impact of Emerging Phishing Threats: Assessing Quishing and LLM-generated Phishing Emails against Organizations
by: Weinz, Marie, et al.
Published: (2025)

MemoPhishAgent: Memory-Augmented Multi-Modal LLM Agent for Phishing URL Detection
by: Chen, Xuan, et al.
Published: (2026)

Phishing Codebook: A Structured Framework for the Characterization of Phishing Emails
by: Saka, Tarini, et al.
Published: (2024)

PhishIntentionLLM: Uncovering Phishing Website Intentions through Multi-Agent Retrieval-Augmented Generation
by: Li, Wenhao, et al.
Published: (2025)

Bridging the Gap in Phishing Detection: A Comprehensive Phishing Dataset Collector
by: Kulkarni, Aditya, et al.
Published: (2025)

PhishSSL: Self-Supervised Contrastive Learning for Phishing Website Detection
by: Li, Wenhao, et al.
Published: (2025)

GuardPhish: Securing Open-Source LLMs from Phishing Abuse
by: Mishra, Rina, et al.
Published: (2026)

PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection
by: Cao, Tri, et al.
Published: (2024)

PhishIntel: Toward Practical Deployment of Reference-Based Phishing Detection
by: Li, Yuexin, et al.
Published: (2024)

PhishingHook: Catching Phishing Ethereum Smart Contracts leveraging EVM Opcodes
by: De Rosa, Pasquale, et al.
Published: (2025)

Phishing Webpage Detection: Unveiling the Threat Landscape and Investigating Detection Techniques
by: Kulkarni, Aditya, et al.
Published: (2025)

PhishGuard: A Multi-Layered Ensemble Model for Optimal Phishing Website Detection
by: Ovi, Md Sultanul Islam, et al.
Published: (2024)

SolPhishHunter: Towards Detecting and Understanding Phishing on Solana
by: Li, Ziwei, et al.
Published: (2025)

EIP-7702 Phishing Attack
by: Qi, Minfeng, et al.
Published: (2025)

Phish-Blitz: Advancing Phishing Detection with Comprehensive Webpage Resource Collection and Visual Integrity Preservation
by: Hriday, Duddu, et al.
Published: (2025)

E-PhishGen: Unlocking Novel Research in Phishing Email Detection
by: Pajola, Luca, et al.
Published: (2025)

PhishNet: A Phishing Website Detection Tool using XGBoost
by: Kumar, Prashant, et al.
Published: (2024)

PEEK: Phishing Evolution Framework for Phishing Generation and Evolving Pattern Analysis using Large Language Models
by: Chen, Fengchao, et al.
Published: (2024)

PhishKey: A Novel Centroid-Based Approach for Enhanced Phishing Detection Using Adaptive HTML Component Extraction
by: Castaño, Felipe, et al.
Published: (2025)

SoK: Exposing the Generation and Detection Gaps in LLM-Generated Phishing
by: Chen, Fengchao, et al.
Published: (2025)

CLASP: Cost-Optimized LLM-based Agentic System for Phishing Detection
by: Trad, Fouad, et al.
Published: (2025)

User-Centric Phishing Detection: A RAG and LLM-Based Approach
by: Barwani, Abrar Hamed Al, et al.
Published: (2026)

LLM-Powered Intent-Based Categorization of Phishing Emails
by: Eilertsen, Even, et al.
Published: (2025)

Phishing Awareness via Game-Based Learning
by: Rahartomo, Argianto, et al.
Published: (2025)

Characterizing Phishing Pages by JavaScript Capabilities
by: Nahapetyan, Aleksandr, et al.
Published: (2025)

Characterizing the Networks Sending Enterprise Phishing Emails
by: Luo, Elisa, et al.
Published: (2024)

Characterizing Phishing Threats with Natural Language Processing
by: Kotson, Michael C., et al.
Published: (2015)

Automated Phishing Detection Using URLs and Webpages
by: Wang, Huilin, et al.
Published: (2024)

Talking Like a Phisher: LLM-Based Attacks on Voice Phishing Classifiers
by: Li, Wenhao, et al.
Published: (2025)

Anti-Phishing Training (Still) Does Not Work: A Large-Scale Reproduction of Phishing Training Inefficacy Grounded in the NIST Phish Scale
by: Rozema, Andrew T., et al.
Published: (2025)