#Tag · Bonfire Dinteg Labs

Random Geek and 1 other boosted

Jürgen Hubert

2/ Okay, I think I might already have some ideas.

My latest #Apache log has 26,694 lines.

In these 26.694 lines, I have:

- 10,724 access requests from "https://developers.facebook.com/docs/sharing/webmasters/crawler"
- 4.562 access requests from "https://developer.amazon.com/support/amazonbot"
- 3.316 access requests from "https://openai.com/gptbot"

So yeah, I suspect these are the #LLM crawling bots from #Facebook , #Amazon , and #OpenAI who jointly make up for more than half the traffic - and they are hogging the more resource intensive functions, like "Recent Changes" on my wiki.

Fuck those fuckers for causing outages on my websites.

And any suggestions on how to block them (no snark, please - I _am_ new at this.)

OpenAI Platform

Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.

Developer Portal Master

About AmazonBot

Customer facing page of Amazonbot crawler which all web content publishers can refer to.

Meta Web Crawlers

This page lists the User Agent (UA) strings that identify Meta’s most common web crawlers and what each of those crawlers are used for.

Jürgen Hubert

@juergen_hubert@mementomori.social · 2 days ago

1/ I have a problem, which is: My websites (a #Wordpress site and a #MediaWiki installation) are slow as hell.

So I need to identify the cause. The problem is that I don't know nearly as much about website administration as I ought to be.

I contacted the support people at my website provider, who looked at my (Apache) logs and suggested that my Wordpress site might suffer from a "pingback xmlrpc attack". I did the proposed remedy, which made things a little better. But I don't know enough about reading website logs to identify such problems myself, which I ought to.

So what I am trying to say is: Is there some kind of beginners guide for reading website logs, identifying malicious traffic, and what to do about it?

Jürgen Hubert

@juergen_hubert@mementomori.social replied · 2 days ago

2/ Okay, I think I might already have some ideas.

My latest #Apache log has 26,694 lines.

In these 26.694 lines, I have:

Fuck those fuckers for causing outages on my websites.

And any suggestions on how to block them (no snark, please - I _am_ new at this.)

OpenAI Platform

Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.

Developer Portal Master

About AmazonBot

Customer facing page of Amazonbot crawler which all web content publishers can refer to.

Meta Web Crawlers

This page lists the User Agent (UA) strings that identify Meta’s most common web crawlers and what each of those crawlers are used for.

Schneier on Security RSS

@Schneier_rss@burn.capital · 2 days ago

Agentic AI’s OODA Loop Problem

The OODA loop—for observe, orient, decide, act—is a framework to understand decision-making in adversarial situations. We apply the same framework to artificial intelligence agents, who have to make their decisions with untrustworth... https://www.schneier.com/blog/archives/2025/10/agentic-ais-ooda-loop-problem.html

#Uncategorized #integrity #LLM #AI

Schneier on Security

Agentic AI’s OODA Loop Problem - Schneier on Security

The OODA loop—for observe, orient, decide, act—is a framework to understand decision-making in adversarial situations. We apply the same framework to artificial intelligence agents, who have to make their decisions with untrustworthy observations and orientation. To solve this problem, we need new systems of input, processing, and output integrity. Many decades ago, U.S. Air Force Colonel John Boyd introduced the concept of the “OODA loop,” for Observe, Orient, Decide, and Act. These are the four steps of real-time continuous decision-making. Boyd developed it for fighter pilots, but it’s long been applied in artificial intelligence (AI) and robotics. An AI agent, like a pilot, executes the loop over and over, accomplishing its goals iteratively within an ever-changing environment. This is Anthropic’s definition: “Agents are models using tools in a loop.”...

@reiver ⊼ (Charles) :batman:

@reiver@mastodon.social · 2 days ago

X (formerly Twitter)

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From @elonmusk@twitter.com:

"""
The 𝕏 recommendation system is evolving very rapidly. We are aiming for deletion of all heuristics within 4 to 6 weeks.

Grok will literally read every post and watch every video (100M+ per day) to match users with content they’re most likely to find interesting.

This should address the new user or small account problem, where you post something great, but nobody sees it.

We will also be adding the ability for you to adjust your feed temporarily or permanently just by asking Grok.
""" — From @elonmusk@twitter.com: """ The 𝕏 recommendation system is evolving very rapidly. We are aiming for deletion of all heuristics within 4 to 6 weeks. Grok will literally read every post and watch every video (100M+ per day) to match users with content they’re most likely to find interesting. This should address the new user or small account problem, where you post something great, but nobody sees it. We will also be adding the ability for you to adjust your feed temporarily or permanently just by asking Grok. """

Music Channel boosted

TiT4NiUm 🎃

@titanium@piaille.fr · 4 days ago

Je suis un grand fan de #Borrtex 🎹 depuis de nombreuses années. Sa dernière création, un petit documentaire sur son histoire personnelle m'inspire deux choses. La première, c'est la fascination pour un artiste talentueux, autodidacte, authentique et sincère. La seconde c'est une forme de tristesse. On vit une époque dans laquelle les artistes doivent ou se sentent obligé de justifier de leur créativité, de leur travail pour ne pas se retrouver accusé d'utiliser un #llm

https://www.youtube.com/watch?v=6WUmPJ50c2w

#musique 🎵 #artist

TiT4NiUm 🎃

@titanium@piaille.fr · 4 days ago

https://www.youtube.com/watch?v=6WUmPJ50c2w

#musique 🎵 #artist

Em :official_verified: boosted

The New Oil

@thenewoil@mastodon.thenewoil.org · 5 days ago

The hidden risks of #AI chat logs and what you’re really giving away

https://proton.me/blog/ai-chat-logs

#privacy #LLM

The New Oil

@thenewoil@mastodon.thenewoil.org · 5 days ago

The hidden risks of #AI chat logs and what you’re really giving away

https://proton.me/blog/ai-chat-logs

#privacy #LLM

Flipboard Tech Desk

@TechDesk@flipboard.social · last week

How easy is it to "poison" a large language model's data? Much easier than experts previously thought. New research from the Alan Turing Institute indicates that only 250 documents are needed to be inserted in order to manipulate a model's behavior. Here's more from institute's blog, including a link to the original paper.

https://flip.it/Dz8pC3

#Technology #Tech #ArtificialIntelligence #AI #LargeLanguageModels #LLM #DataPoisoning