One person, a hundred accounts, a hundred different fingerprints
Anti-detect browsers are commercial products with a single job: give every profile a borrowed identity. Hardware, fonts, GPU, timezone, screen — fabricated per profile, each profile behind its own proxy. To your systems, one operator on one laptop looks like a hundred unrelated people on a hundred unrelated devices.
You cannot see the person behind the profiles. You can see the tool. Tracio recognizes 20 anti-detect builds by name, and a separate signal catches the act of fingerprint spoofing itself — including products that have never appeared on anyone's list.
anti-detect builds recognized by name
signals watching for fingerprint spoofing
device signals behind every visit
Built so that every profile looks like a different person
A normal browser has one fingerprint because it sits on one machine: one GPU, one set of fonts, one audio stack, one screen. An anti-detect browser cuts that link. You buy a subscription, create a profile, and the profile gets its own fabricated hardware, its own timezone, its own WebGL vendor, its own proxy. Profiles are saved, shared across a team, exported and resold like any other working asset.
Multi-accounting
Dozens or hundreds of accounts on one marketplace, exchange or ad platform, all operated from a single machine by a single person or team.
Ban evasion
A blocked account is back within minutes as a fresh profile: new fingerprint, new proxy, new browser identity, same operator.
Promo and bonus abuse
Sign-up bonuses, first-deposit offers, free trials and referral rewards farmed at scale. Budget meant for hundreds of new customers goes to one.
Affiliate and referral fraud
Self-referrals and manufactured conversions, where the affiliate and the newly acquired user are the same person on the same laptop.
Not everyone who runs one is committing fraud, and the product is built to make that distinction rather than flatten it.
Two levels, on purpose
Recognizing named products and recognizing the technique are different problems, and Tracio does both. One of the two ages; the other does not.
By name
Twenty builds are identified individually. Each ships its own patched engine and leaves its own residue while it rewrites what a page is allowed to see, so when the tool can be named, it is named — not merely flagged as something unusual.
By the spoofing mechanism
A list of products starts ageing the moment it is published. The second signal does not look for a product at all: it looks for the act of spoofing — values that contradict each other, APIs answering the way no physical device answers, a machine whose parts belong to different machines. A build released next month, or a private in-house tool that was never sold to anyone, is caught by the same signal the day it first shows up in your traffic.
Recognized by name
- Dolphin Anty
- GoLogin
- Multilogin
- Mimic
- Kameleo
- Linken Sphere
- AdsPower
- Octo Browser
- Incogniton
- Undetectable
- and 10 more builds
Mullvad Browser is treated differently — deliberately
Mullvad is a privacy browser, not a multi-accounting tool. It resists fingerprinting because that is the entire point of it, and the people using it are usually protecting themselves rather than running fifty seller accounts. It is reported like anything else, but it carries far less weight than a commercial anti-detect build. A privacy-conscious customer is still a customer, and treating them as a fraud ring is its own kind of mistake.
It shows up where you already look
In the visit record
Open a visitor and it is stated plainly: this session came through an anti-detect browser — and which build, when the build can be named.
In analytics
Count and filter it like any other property. How much of last month's sign-up traffic arrived on spoofed fingerprints, which campaigns attracted it, which hours it clusters in.
In webhooks
Every event delivered to your backend carries the signal, so your own rules can react while the session is still open.
In the Data API
Query it after the fact — for one visitor, for a cohort, or for the month you are writing a chargeback report about.
Tracio hands you the evidence; your rules decide what it is worth. The same finding justifies step-up verification at sign-up on one site, a manual review queue for high-value orders on another, and nothing at all on a third — so the signal is delivered everywhere you can act on it, and the policy stays yours.
Wherever one account per person is the assumption
Marketplaces
Seller networks run from one desk, review rings, and buyer accounts that reappear the day after a ban.
iGaming and betting
Bonus farming, several seats at the same table, and accounts that come back after a self-exclusion request.
Fintech and crypto
Onboarding farms where dozens of customers share one operator, and payout schemes built on the same trick.
Promo campaigns
Sign-up credit, free trials and first-order discounts, where a handful of operators can absorb a budget meant for thousands.
Affiliate programs
Self-referrals and fabricated conversions that pass for organic growth until the tooling behind them becomes visible.
Frequently asked questions
See the tooling behind the accounts
Twenty anti-detect builds recognized by name, the spoofing mechanism caught regardless of brand, and 300+ device signals behind every visit.