Using LLMs to shortcut critical thinking is sometimes a cheat code and sometimes a stupid idea, it depends.

Now that we have thinking models and methodology to train them, surely before long it will be possible to have a model that is very good at the kind of thinking that an expert OSINT analyst knows how to do.

There are so many low hanging fruit applications of existing LLM strengths that have simply not been added to the training yet, but will be at some point.

Why OSINT? That goes for any domain.

Besides "OSINT" has been busy posting scareware for years, even before "AI".

There's so much spam that you can't figure out what the real security issues are. Every other "security article" is about "an attacker" that "could" obtain access if you were sitting at your keyboard and they were holding a gun to your head.

I question the notion that such tools are necessary or admissible in my daily life.

Mere observation of others has shown me the decadence that results from even allowing such "tools" into my life at all.

(who or what is the tool being used?)

I have seen zero positive effects from the cynical application of such tools in any aspect of life. The narrative that we "all use them" is false.

> Not because analysts are getting lazy, but because AI is making the job feel easier than it actually is.

But all the examples feel like people are being really lazy, e.g.

> Paste the image into the AI tool, read the suggested location, and move on.

> Ask Gemini, “Who runs this domain?” and accept the top-line answer.

I'd argue that for a profession that has existed for quite some time, "since chatGPT appeared" isn't in any way "slow"

Tried one exercise from the article, to ask gemini to identify owner of domain (my domain). Gemini was very confident and very wrong.

I bet any OSINT person would have had my name and contact in half an hour.

> What Dies When Tradecraft Goes Passive?

Eventually, Brazil (1985) happens, to the detriment of Archibald [B]uttle, where everyone gives unquestionable trust to a flawed system.

Aka, i have no problem being explicitly anti AI as a bad idea to begin with. This is what I think, that it is a foolish project from the get go.

Techne is the Greek word for HAND.

Most cybersecurity is just a smoke show anyways, presentation matters more than content. AI is just good at security theather as humans are.

OSINT is a symptom of it. When GPT-2 came along, I was worried that at some point the internet will get spammed with AI-crap. Boy, was I naive... I see this incredibly frequently and I get a ton of hate for saying this (including here on HN): LLMs and AI in general is a perfect demonstration of a shiny-new-toy. What people fail to acknowledge is that the so called "reasoning" is nothing more then predicting the most likely next token, which works reasonably well for basic one-off tasks. And I have used LLMs in that way - "give me the ISO 3166-1 of the following 20 countries:". That works. But as soon as you throw something more complex and start analyzing the results(which look reasonable at first glance), the picture becomes very different. "Oh just use RAGs, are you dumb?", I hear you say. Yeah?

class ParsedAddress(BaseModel):

    street: str | None

    postcode: str | None

    city: str | None

    province: str | None

    country_iso2: str | None

Response:

{

  "street": "Boulevard",

  "postcode": 12345,

  "city": "Cannot be accurately determined from the input",

  "province": "MY and NY are both possible in the provided address",

  "country_iso2": "US"

}

Sure, I can spend 2 days trying out different models and tweaking the prompts and see which one gets it, but I have 33 billion other addresses and a finite amount of time.

The issue occurs in OSINT as well: A well structured answer lures people into a mental trap. Anthropomorphism is something humans have fallen for since the dawn of mankind and is doing so yet again with AI. The thought that you have someone intelligent nearby with god-like abilities can be comforting but... Um... LLMs don't work like that.