Last updated: October 12, 2026 · Category: How-To Guide · Editorial review · About the authors
Key Takeaways
- The clearest audit signal is timing: a cluster of accounts joining within a short window, especially right around a reward announcement.
- An audit does not require anti-fake to have been on the whole time. Account creation dates and join timestamps are still visible after the fact.
- Finding fakes after the fact means excluding them manually once, then setting a threshold so future joins filter automatically.
Anti-fake filtering works going forward. It does not retroactively clean up a leaderboard that has already been running without it. If you suspect farming already happened, an audit answers the question directly instead of guessing from the final numbers.
This is the one piece missing from the site's existing anti-fake coverage: what prevention explains and what detection classifies both assume you are looking forward. An audit looks backward, at joins that already happened and already counted.
Step 1: Pull Your Full Invite Timeline
Build a join timeline before you judge the leaderboard totals. A join timeline is the ordered list of attributed joins with their timestamps and inviters, and it is the raw material an audit actually needs. On desktop or browser, Discord's own Members page (retrieved 2026-10-12) is the most direct source: filter by Members Since for the window you suspect, then by Joined Discord, for account age, and Join Method, for the invite code each member used. Seeing invite codes there needs the Manage Server permission. In InviteForge, /invites shows each member's real, fake, left, bonus, and net invites, and Dashboard → Analytics charts real and fake joins over the selected period: 24 hours or 7 days on the free plan, 14 days on Supporter, and 30 days on PRO. The Live feed tab only shows events that arrive while it is open, so it helps during a spike, not for joins that already happened. The leaderboard alone hides the pattern; the timeline shows it.
Step 2: Find the Timing Cluster
Farming has a distinctive shape: a burst of joins concentrated in a short window, usually within a day or two of a reward being announced. Real organic growth is comparatively spread out. Sort your timeline by join date and look for any inviter whose count jumped sharply in a narrow window rather than accumulating steadily.
This step alone catches most farming, since coordinated alt accounts are almost always created and joined together rather than spread naturally across weeks.
Step 3: Check Account Creation Dates Against Join Dates
For any inviter flagged in Step 2, check the account creation date of the accounts they brought in. Every Discord account ID encodes its creation timestamp directly in the snowflake ID itself, retrieved 2026-09-09, which is what makes account age checkable at all, visible from the account's own profile or, in bulk, through a bot with account-age detection.
A short gap between account creation and server join, especially clustered across many accounts from the same inviter, is the strongest confirmation. A wide, varied gap suggests the accounts are older and the pattern deserves a second look before concluding they are fake.
Step 4: Exclude and Reset
Once you have confirmed which joins were farmed, remove them from the counts that feed the leaderboard and any pending rewards. The InviteForge docs list two correction commands: /bonus remove <user> <amount> [reason] subtracts invites from one member's total, and /reset-invites (Administrator) resets one member or the whole server. This is a manual, one-time cleanup for joins that already happened before filtering was in place.
Step 5: Set a Threshold Going Forward
An audit fixes what already happened. It does not stop it from happening again. Set an account-age anti-fake threshold sized to your actual reward stakes, so the next audit finds nothing to clean up.
Frequently Asked Questions
How do I know if my Discord leaderboard has been farmed?
Look for a cluster of accounts near the top of your leaderboard that all joined within a short window, especially right before or after a reward was announced. That timing pattern is the clearest signal.
Can I audit a server that never had anti-fake filtering on?
Yes. Turning on account-age filtering does not retroactively reclassify past joins, but you can still manually review the join timeline and account creation dates for existing top inviters.
What do I do with accounts I find are fake?
Exclude them from the leaderboard and any pending rewards, then set an anti-fake threshold going forward so new joins get filtered automatically instead of needing manual review.
How often should I audit my invite data?
Right after any reward announcement, since that is when farming incentives spike. Outside of that, a monthly spot-check of your top inviters is enough for most servers.