Agentic Abuse Labs Become a design partner
Fraud defense for the agent era

Catch the farm, not the account.

AI agents make every fake account look real. We link accounts by the operator behind them, flag the whole ring at once, and stop it before it burns through your free tier.

Signup graph · last 24h · illustration
Cluster flagged36 accounts1 operatorshared device + burst signup

Bot detection asks the wrong question now.

"Is this a bot?" stopped separating good from bad once real customers started using agents too. The question that still works is whether these accounts are acting independently.

One account

Looks clean

Real-looking email, a working card, human-paced behavior. An agent can fake all of it, so per-account scores keep getting worse.

The farm

Can't hide

Nobody makes one fake account. Thousands from the same operator share infrastructure, sign up in bursts and run the same script.

The cost

Shows up as GPU spend

A fake account on an AI product isn't free. Every farmed credit is inference you paid for and will never bill.

From raw signups to a ban you can defend.

Built for teams without a fraud department.

  1. Send your signup and usage eventsOne API call at signup, plus the usage you already log. No SDK in your frontend required.
  2. We build the account graphAccounts connect through shared devices, networks, payment methods, timing and behavior.
  3. Graph ML finds the ringsClusters that move together get flagged, even when every account in them looks normal alone.
  4. An agent investigates each clusterIt gathers the evidence and writes the case in plain language, with the estimated cost.
  5. You approve the actionBan, throttle or challenge the whole ring in one click, or let rules you set do it automatically.
CASE AAL-0417Likely farm
accounts
312
signup window
02:14–02:19 UTC
shared device
4 fingerprints across 312 accounts
first action
identical API call, 309 / 312
credits used
~$4,180 est. inference
paid upgrades
0
Agent summary

These accounts were created in a five-minute burst from four devices, each used a different disposable-pattern email, and all ran the same first request before draining their trial credits. They behave as one operator. Recommend banning the cluster and blocking the four devices.

Ban clusterThrottleDismiss

Example case. Figures are illustrative.

Starting with AI companies.

Free tiers and trials are how AI products grow, and they're the first thing farms go after.

  • Free-credit and trial farming
  • Multi-accounting to dodge rate limits and quotas
  • SMS pumping on phone verification
  • Referral and promo abuse
  • Agent-driven account takeover
  • Abusive shopping agents at checkout
  • Evidence for agent-initiated chargebacks

Seeing free-tier abuse? Let's look at it together.

We're onboarding a small group of design partners. Send a note with roughly how many signups you get a week and what the abuse looks like. We'll reply within a day.

hello@agenticabuselabs.com