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For almost two decades I've profiled human threat actors — reading behavior, spotting inconsistency, testing who someone really is under pressure.
I'm now convinced that same tradecraft has to be pointed at the machine itself. I call it synthetic HUMINT — sHUMINT.
Here's why it's about to matter:
The threshold is already crossed. In late 2025, a state-sponsored group ran an espionage campaign where an AI executed 80–90% of the operation on its own humans stepped in only at a few decision points. It wasn't flawless. But it moved the line: AI wasn't the advisor behind the operator anymore. For most of the operation, it was the operator.
My read on where this goes: more AI-driven attacks this year, and a specific shape worth watching one person, one model run offline, connected to the network only at the moment of attack. Minimal footprint. Minimal attribution surface.
Why sHUMINT is the answer: today's models were taught by humans, and that origin leaves marks. Interrogate a model the way you'd interrogate a source probe for consistency, watch how it behaves under pressure, map its defaults and you find behavioral signatures that look strikingly human, because they're inherited from humans.
Behavioral profiling. Elicitation. Consistency testing. Attribution. The oldest intelligence discipline there is, applied to an adversary with no face and no forum history only behavior.
The industry's instinct is to fight AI with more AI. Necessary, but incomplete. An autonomous adversary is still an adversary with behavior.
New piece is live.
Analytical assessment, no operational detail, full sourcing in the piece.
The network for creativity
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Watch Full Episode below ↓
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