I certainly want them to crawl to the extent possible. One of the main 
problems using LLMs for coding is that APIs change. It is less of a problem now 
that it was a month ago. Now they all have integrated web search. 

From: Friam <[email protected]> on behalf of glen <[email protected]>
Date: Friday, March 28, 2025 at 10:05 AM
To: [email protected] <[email protected]>
Subject: Re: [FRIAM] the basilisk 

Exactly. I tend to think that if an AI is truly I, it will *welcome* such ... 
like a meta-honorable duel. I'm currently watching "The Madness", which 
characterizes AntiFa as "sociopathic murderers" ... like with words you'd 
describe O9A or 764. And I guess that fits what many on the right think, maybe. 
But it's so silly. I feel like the basilisk will understand Tzu and Machiavelli.

On 3/28/25 9:40 AM, Marcus Daniels wrote:
> Let’s ask one of the LLMs how they would defeat it:
> 
> To "defeat" iocaine means either avoiding its trap as an AI crawler or 
> detecting and filtering out its garbage content. Here are some practical 
> approaches:
> 
> 1. *Identify and Avoid the Reverse Proxy Trap*
> * *How it works*: Iocaine relies on a reverse proxy (e.g., nginx or Caddy) to 
> route AI crawlers to its garbage generator based on user-agent strings (like 
> "GPTBot" or "Claude") while serving real content to others.
> * *Defeat strategy*: Mask your crawler’s identity by using a generic or 
> human-like user-agent string (e.g., mimicking a common browser like 
> "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"). 
> Additionally, randomize headers, IP addresses, and request patterns to blend 
> in with legitimate traffic. Proxies and residential IP pools can help obscure 
> your crawler’s footprint, making it harder for the reverse proxy to single 
> you out.
> 2. *Detect Deterministic Garbage*
> * *How it works*: Iocaine’s content is stable per URL due to its seeded 
> random number generator. This predictability is a double-edged sword—it’s 
> consistent for tarpit purposes but distinguishable from truly dynamic or 
> human-generated content.
> * *Defeat strategy*: Analyze the content’s structure and consistency over 
> time. Fetch the same URL multiple times; if the response is identical despite 
> no apparent reason for static behavior (e.g., it’s not a cached page), it’s 
> likely iocaine-generated. Compare text entropy or linguistic patterns—Markov 
> chain output often lacks the semantic depth of human writing and may exhibit 
> repetitive or unnatural transitions.
> 3. *Exploit the Lack of External Context*
> * *How it works*: Iocaine’s pages don’t link to external sites, creating an 
> isolated ecosystem of garbage. Real websites typically connect to broader web 
> structures.
> * *Defeat strategy*: Check for outgoing links. If a page only links to itself 
> or similar internal paths (e.g., using words from a predictable wordlist like 
> "wamerican.txt"), flag it as suspicious. Cross-reference with known 
> legitimate domains or crawl broader site sections to see if the content 
> aligns with the site’s supposed purpose.
> 4. *Leverage Rate Limiting Weaknesses*
> * *How it works*: Many iocaine deployments pair it with rate limiting (e.g., 
> 16 requests/minute) to slow crawlers, but this is handled by the reverse 
> proxy, not iocaine itself.
> * *Defeat strategy*: Distribute your crawling across multiple IPs or slow 
> your request rate to stay under the threshold. If you’re avoiding detection 
> anyway (per strategy 1), rate limits may not even apply, as you’ll be treated 
> as a legitimate user.
> 5. *Train AI to Recognize Iocaine Patterns*
> * *How it works*: Iocaine uses a Markov chain trained on arbitrary texts 
> (e.g., the Bee Movie script) and a wordlist for links, producing content 
> that’s coherent on a surface level but semantically hollow.
> * *Defeat strategy*: Build a classifier to spot iocaine-like output. Train it 
> on samples from iocaine’s demo site (https://iocaine.madhouse-project.org/ 
> <https://iocaine.madhouse-project.org/ 
> <https://iocaine.madhouse-project.org/>>) versus real web content. Look for 
> features like low semantic coherence, repetitive link patterns, or an absence 
> of meaningful metadata (e.g., no real authorship or timestamps).
> 
> *From: *Friam <[email protected]> on behalf of glen 
> <[email protected]>
> *Date: *Friday, March 28, 2025 at 9:21 AM
> *To: *[email protected] <[email protected]>
> *Subject: *[FRIAM] the basilisk
> 
> If it's punishing those who don't actively work to promote it, what's it 
> doing to folks like these? >8^D
> 
> https://git.madhouse-project.org/iocaine/iocaine 
> <https://git.madhouse-project.org/iocaine/iocaine> 
> <https://git.madhouse-project.org/iocaine/iocaine 
> <https://git.madhouse-project.org/iocaine/iocaine>>
> 
> And for those of us who like to reify metaphor: 
> https://link.springer.com/article/10.1007/s13181-014-0385-4 
> <https://link.springer.com/article/10.1007/s13181-014-0385-4> 
> <https://link.springer.com/article/10.1007/s13181-014-0385-4 
> <https://link.springer.com/article/10.1007/s13181-014-0385-4>>
> 


-- 
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