Sybil checks in points programs: what they measure and why you should assume filters

December 30, 2025 · 5 min read

A practical explanation of sybil resistance in points programs: common signals, why filters exist, and how to avoid betting on assumptions.

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Table of contents

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If you’re farming points, assume filters exist. Many programs award points in real time, then apply eligibility checks later. That creates a trap: you can feel “ahead” while you’re quietly building a strategy on assumptions.

This post explains what “sybil checks” usually try to detect, why protocols use them, and how to build a plan that doesn’t require you to outsmart filters.

This is not advice on evasion. If a program has rules, follow them.

Browse sourced campaigns here: points directory.

Quick take

Sybil checks exist to prevent one actor from capturing rewards meant for many users.
Filters are often applied after the fact; points earned today aren’t guaranteed eligible later.
Programs rarely publish exact filters; treat uncertainty as real.
Build a strategy that still makes sense if you earn fewer points than expected.
Don’t scale based on “multi-wallet math” you can’t verify.

What “sybil” means in this context

A “sybil” attack is when one actor pretends to be many independent users to capture outsized rewards. In points programs, that often looks like:

many wallets funded and controlled by one entity
repetitive patterns that look automated
activity that exists only to harvest incentives

Protocols try to discourage this because it can:

distort growth metrics
drain incentive budgets without creating real users
create backlash when rewards feel unfair

Why you should assume filters (even if none are stated)

As of 2025-12-30, many programs do not publish exact sybil filtering logic because:

publishing exact rules makes them easier to game
detection relies on multiple signals that change over time

So you should treat sybil filtering as a background uncertainty, similar to:

changes in scoring weights
changes in eligibility requirements

This isn’t a reason to panic. It’s a reason to avoid strategies that only work if filters don’t exist.

The common misread: points ≠ eligibility

It’s normal to see a points dashboard and assume it means “I’m in.” Often, it only means “the app tracked activity.” Eligibility can still be filtered later.

Treat “points displayed” as a progress bar, not as proof of future rewards.

Common signals programs look at (high level)

This is intentionally high level. The goal is to understand uncertainty, not to help anyone evade rules.

Signal type	What it can indicate	Why it matters
Funding patterns	Many wallets funded from the same source	Links wallets to a single controller
Timing patterns	Highly repetitive activity timing	Suggests automation or coordination
Interaction graph	Wallets that only touch incentive routes	Suggests incentive-only behavior
Volume shape	Wash volume and circular routes	Inflates metrics without real demand
Duration	Very short holds or instant exits	Captures points with minimal exposure

Even if you behave normally, you can still get filtered by broad heuristics. That’s why sizing and exit planning matter.

If you want a framework for comparing programs without assumptions, read: compare crypto points programs.

The safer way to think about points under uncertainty

When eligibility is uncertain, use this mental model:

Points are not a claim on rewards.
Points are a meter the protocol controls.
The protocol can change what “counts.”

So your strategy should be:

low operational complexity
easy to unwind
sized so a full loss is survivable

More on exits: points farming exit plan.

What you can verify (and what you can’t)

You can often verify:

whether a points program is real (primary sources)
the actions the UI asks you to do
the basic costs (fees, gas, bridge routes)

You often can’t verify:

exact sybil filters
how scoring weights are applied across users
whether points convert into token rewards

Labeling the unverified parts is part of being accurate.

For sourcing hygiene, read: how to verify a points program is real.

FAQ

Are sybil checks “anti-user”?

Not inherently. They’re a way to keep incentive budgets from being captured by a small number of actors. The implementation can still be messy.

Can I know if I will be filtered?

Usually not with certainty. Programs rarely publish full filters. Assume uncertainty and avoid strategies that depend on perfect eligibility.

Are multiple wallets always forbidden?

Rules differ by program. Some explicitly forbid it, some tolerate it, and some target specific abusive patterns. Follow the published rules and avoid assumptions.

What’s the safest approach under sybil uncertainty?

Keep strategies simple, sourced, and easy to unwind. Don’t scale based on rumors about “what counts.”

If filters exist, should I stop participating?

Not automatically. It means you should avoid scaling based on assumptions. Keep exposure small, keep workflows simple, and treat points as optional upside until rules are sourced.