Dolphin{anty} Detection

How to detect Dolphin{anty} in 2026

Dolphin{anty} is an antidetect browser built for teams that run large numbers of accounts in parallel — it comes up constantly in affiliate marketing and media-buying circles, and on the defence side it's a recurring name in bonus-abuse and account-farming investigations. Sentinel scores its sessions the way it scores any masked device: engine consistency, automation, network origin, and reuse history.

What Dolphin{anty} is

Dolphin{anty}'s own marketing is workflow-first: a Chromium-based antidetect engine, a free plan with a handful of profiles, and paid tiers priced by profile count. Its distinguishing features are operational — profile statuses, tags, and notes so a team can divide hundreds of accounts between members, bulk proxy assignment, and built-in automation through scriptable scenarios and an API. That feature set describes the workload precisely: many synthetic identities, worked by several people, on schedule.

How Sentinel reads a Dolphin{anty} session

No single check decides the verdict. A Dolphin{anty} session presents a fabricated device over a rented network path, usually with software doing the clicking — and each of those three lies is tested by a different, independent layer of the pipeline.

Antidetect signal

Sentinel's device layer identifies the traits antidetect engines share — a fingerprint surface rebuilt to be configurable — and reports device.antidetect with reason code antidetect_browser, regardless of which profile is loaded.

Tampering score & profile coherence

device.tampering_score (0–1) rises when the profile's claims disagree with reality: engine behaviour that doesn't match the claimed browser version, platform internals that contradict the claimed OS. Scores above 0.6 are strong evidence; 0.3–0.6 flags looser inconsistencies.

Scenario automation trips the bot signal

Dolphin{anty}'s scenarios and API exist to run profiles without a human at the keyboard. That's exactly the behaviour device.automation detects, surfacing the automation_detected reason code.

Virtual machines

Teams parcelling out profile batches often work from VMs or rented desktops. device.virtual_machine and device.emulator flag the host independently of the browser profile riding on it.

Spur network layer

Bulk proxy management is a core Dolphin{anty} feature because every profile needs its own exit. Sentinel's Spur-powered layer flags residential proxies and VPNs on the network evidence alone — the device can't talk its way past it.

times_seen & multi-account linking

Farms reuse machines even when they rotate profiles. device.times_seen counts appearances of the underlying device, and passing accountId lets linked_accounts reveal one device behind a crowd of signups — the multi_account signal.

Straight answer on accuracy: some Dolphin{anty} sessions will look clean on first contact — no vendor detects every antidetect session every time, and claims otherwise deserve suspicion. Layering is the counter: the operator has to pass device, automation, network, and history checks together, and repeat that success on every visit. Sentinel exposes each signal and a 0–100 score so your rules make the final call.

Shipping it

Put the Sentinel SDK on signup, login, and bonus-claim flows, then call /v1/evaluate server-side. The response's device and network blocks carry everything above. Field-by-field docs live in the API reference; the technique is unpacked in the antidetect detection deep-dive. For the tool-specific breakdown, see Dolphin{anty} test diary: the signals that refused to spoof.

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