For seventeen years, a vulnerability sat in FreeBSD.
An AI found it in an afternoon.

The attacker on the other end of your perimeter is no longer a human with a notebook of TTPs. Increasingly, it's an autonomous agent that can read your repos, infer your architecture, draft an exploit and adapt mid-session — at machine speed, in parallel, without fatigue.

Traditional SIEMs were never built for this. They raise thousands of probabilistic alerts your team has hours, not seconds, to triage. By the time someone has read the first line of the ticket, the agent has already finished its work.

{/* soft blue corner glow */}

// THE VANTUZ THESIS

Probability detection cannot outrun autonomous attack.
Deception can.

A honeytoken has no false positive. No legitimate user reads a fake AWS key. No internal service queries a decoy database. Every touch is, by construction, an attacker — human or otherwise. That single property is what makes deception the only detection model that survives contact with autonomous adversaries.

{/* the contrast strip */}

{[ { label:'LEGACY SIEM', body:'Generates 11,000 alerts/month. 99.4% noise. Human-only response. Built before LLMs existed.', tone:'var(--txt-3)' }, { label:'VANTUZ', body:'0 noise. Every alert is an attacker. AI pipeline contains in 11s. Built for an adversary that runs on tokens, not coffee.', tone:'var(--aurora-2)' }, ].map((it, i) => (

{it.label}

{it.body}

))}

For seventeen years, a vulnerability sat in FreeBSD. An AI found it in an afternoon.

For seventeen years, a vulnerability sat in FreeBSD.
An AI found it in an afternoon.