Finger: Social network that never died
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en.andros.dev
August 18, 2026
16 min read
53/100
Summary
Finger is a network protocol created at Stanford’s Artificial Intelligence Laboratory in 1971 to show who was using a shared WAITS time-sharing computer, including names, locations and terminal idle time. Ken Harrenstien formalized it in RFC 742 in 1977, and RFC 1288 became its definitive specification in 1991. A Finger client connects to a server’s TCP port 79, sends a username or an empty query, receives plain text, and closes the connection. Finger servers commonly returned users’ .plan and .project text files, originally intended to describe current work and plans. Users turned .plan files into public diaries, technical logs, jokes and other personal publishing. John Carmack used a .plan file from 1996 to 2010 as a development journal and announced plans to release Doom’s source code there on August 18, 1997. Carnegie Mellon students also exposed a Coca-Cola machine’s stock and bottle-cooling data through Finger around 1982. Security and privacy concerns drove Finger’s decline, particularly after the 1988 Morris worm exploited a fingerd buffer overflow. Some systems still include Finger clients, including Windows’ finger.exe, which attackers abused in 2020 to retrieve malware payloads. Current services and software, including Happy Net Box, Finger.Farm and plan.cat, continue to host and modernize .plan-style publishing; plan.cat also bridges Finger posts to ActivityPub.
Key Takeaways
- Finger uses a minimal plain-text protocol over TCP port 79 to return information associated with a requested user or host.
- Users historically published public status updates and diaries in .plan files that Finger servers returned as text.
- The 1988 Morris worm spread partly through a buffer-overflow vulnerability in a fingerd implementation, helping prompt administrators to disable Finger services.
- John Carmack’s archived .plan entries documented game development from 1996 to 2010 and included his 1997 plan to release the Doom source code.
- Happy Net Box, Finger.Farm and plan.cat provide contemporary ways to publish or self-host Finger-based profiles and updates.
What the discussion said
The only substantial AI-related exchange spun off from a reader detecting an AI-like tone in the article’s polished introductory prose. The author’s disclosed use was narrow: using AI for cleanup work such as wording revisions, typo checks, synonym suggestions, code adaptation, and translation between Spanish and English. That disclosure gave the conversation a more nuanced target than outright ghostwriting, though it did not settle whether the surrounding prose sounded machine-assisted. Several commenters pushed back on style-based AI detection. Their core point was that language models reproduce common writing patterns because those patterns were present in their training material; seeing those patterns in a human’s writing therefore proves very little. One reader especially objected to the social cost of this suspicion: writers with eccentric punctuation, unusually polished sentences, or recognizable personal habits can now have their voice treated as evidence against them. Others maintained that certain stylistic signals can still be suggestive, even if they fall far short of proof. The thread did not meaningfully debate AI capability or model quality; it focused on the frailty of informal AI-authorship judgments and on the acceptable boundary between editorial assistance and generated writing.
Where opinion split
The sharpest split is whether a distinctive, polished prose style is meaningful evidence of AI assistance. Skeptics treat recurring punctuation and polished phrasing as a practical warning sign, while others argue that this heuristic punishes human writers precisely because language models have absorbed and copied familiar literary habits.
Community Sentiment
Positives
- Limited AI use for proofreading, translation, and small code or wording adjustments was presented as a practical assist rather than a substitute for authorship.
- The exchange recognizes a useful distinction between mechanical editorial support and handing the actual writing over to a model.
Concerns
- Using punctuation quirks and polished cadence as an AI tell risks turning ordinary human style into a false-positive detector with no reliable evidentiary basis.
- Models trained to imitate widely published prose have made distinctive human writing feel suspicious, unfairly burdening writers whose voice falls outside bland default conventions.
