PhishGen: Understanding LLM Capabilities in Automated Phishing Website Generation
PhishGen systematically measures LLMs' ability to generate functional phishing sites from plain-language prompts, demonstrating that the skill barrier for convincing phishing campaigns is collapsing.
Summary written by editorial AI · Source link below
arXiv:2610.30226v1 Announce Type: new Abstract: Phishing relies on visual deception, traditionally requiring web-development skills or pre-built kits. LLMs erode this barrier by generating functional websites from natural-language prompts, yet prior work does not answer how far LLM-driven generation actually reaches: functionality is assessed by inspection rather than execution; visual fidelity is scored by automated metrics or a few internal coders rather than the humans such pages aim to dece
Editorial Analysis
The commoditisation of phishing-site creation via LLMs means European enterprises should expect higher phishing volumes with fewer telltale quality defects, straining existing detection filters.
Run LLM-generated phishing pages through your email and web-gateway detection stack to identify coverage gaps before attackers exploit them.
LLMs can now generate convincing phishing sites without web-development skills, lowering the barrier for high-volume, high-quality phishing campaigns targeting enterprises.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
More from the Threat Intel Desk
- PHP2Shell Exploitation Hits Government Entity Amid Global Scanning and Signs of AI-Assisted Hacking1d
- BlackX UEFI bootkit exploits Baton Drop flaw to bypass Secure Boot2d
- Trust Is Not What It Seems — And Fraudsters Are Counting on It3d
- AI Tools Are Generating Massive Attacks for Little Cost3d
- The Good, the Bad and the Ugly in Cybersecurity - Week 43 (2026)3d