Sabot in the Age of AI
Here is a curated list of strategies, offensive methods, and tactics for (algorithmic) sabotage, disruption, and deliberate poisoning.
π» iocaine
The deadliest AI poisonβiocaine generates garbage rather than slowing crawlers.
π https://git.madhouse-project.org/algernon/iocaine
π» Nepenthes
A tarpit designed to catch web crawlers, especially those scraping for LLMs. It devours anything that gets too close. @aaron
π https://zadzmo.org/code/nepenthes/
π» Quixotic
Feeds fake content to bots and robots.txt-ignoring #LLM scrapers. @marcusb
π https://marcusb.org/hacks/quixotic.html
π» Poison the WeLLMs
A reverse-proxy that serves diassociated-press style reimaginings of your upstream pages, poisoning any LLMs that scrape your content. @mike
π https://codeberg.org/MikeCoats/poison-the-wellms
π» Django-llm-poison
A django app that poisons content when served to #AI bots. @Fingel
π https://github.com/Fingel/django-llm-poison
π» KonterfAI
A model poisoner that generates nonsense content to degenerate LLMs.
π https://codeberg.org/konterfai/konterfai
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@asrg
if you ever feel up to chatting with me for an episode of The Data Fix (podcast), please let me know ππ½
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@mel_hogan .. Sounds great! Weβd love to chatβweβll let you know! π
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@asrg Im rarely on here but email me anytime: https://www.queensu.ca/filmandmedia/people-search/mel-hogan ππ½
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@mel_hogan Thanks! Weβll reach out via email soon.
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