9 citations · 10 across the 9 of their papers we have counts for
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cs.CR2026
PhishGen: Understanding LLM Capabilities in Automated Phishing Website Generation
Fujiao Ji, Yerim Kim, Yena Cho +3
Phishing relies on visual deception, traditionally requiring web-development skills or pre-built kits. LLMs erode this barrier by generating functional websites from natural-langua…
cs.CR2026
Poster: Mind the Gap -- Characterizing the Temporal Blind Spot Between GSB and DNS Resolution
Tomer Gal, Fujiao Ji, Doowon Kim +1
Google Safe Browsing (GSB) and DNS resolution operate concurrently during browser navigation, yet their packet-level synchronization remains understudied. This work characterizes t…
cs.CR2026
What the Eyes See, the LLMs Miss: Exploiting Human Perception for Adversarial Text Attacks
Qin Yang, Lu Malloy, Joshua Lee +4
Large language model (LLM)-powered content moderation systems are a critical defense against harmful online content. However, they operate primarily on tokenized text and often ove…