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Early Phishing

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arxiv 1106.4692 v1 pith:7WZPID4H submitted 2011-06-23 cs.CR cs.CYcs.SI

classification cs.CRcs.CYcs.SI
keywords phishingautomatedsoftwareaohellavailablebackcomputerfirst
verification ladder T0 review T1 audit T2 compute T3 formal

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The history of phishing traces back in important ways to the mid-1990s when hacking software facilitated the mass targeting of people in password stealing scams on America Online (AOL). The first of these software programs was mine, called AOHell, and it was where the word phishing was coined. The software provided an automated password and credit card-stealing mechanism starting in January 1995. Though the practice of tricking users in order to steal passwords or information possibly goes back to the earliest days of computer networking, AOHell's phishing system was the first automated tool made publicly available for this purpose. The program influenced the creation of many other automated phishing systems that were made over a number of years. These tools were available to amateurs who used them to engage in a countless number of phishing attacks. By the later part of the decade, the activity moved from AOL to other networks and eventually grew to involve professional criminals on the internet. What began as a scheme by rebellious teenagers to steal passwords evolved into one of the top computer security threats affecting people, corporations, and governments.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. LLM-Powered Intent-Based Categorization of Phishing Emails

    cs.CR 2025-06 conditional novelty 5.0 of 10

    On a curated 100-email test set, three of four evaluated LLMs detected phishing intent from email text with 88 to 97 percent accuracy and categorized attacks into link, attachment, or service types.

  2. AI-Powered Spearphishing Cyber Attacks: Fact or Fiction?

    cs.CR 2025-02 reject novelty 4.0 of 10

    In a 44-person test, 66% of audio and 43% of video answers about AI-generated clips were wrong, but those rates include errors on genuine clips and are not clean measures of missed fakes.

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