BrightID · interactive mechanism simulation

New signups connect into a pseudonymous social graph → a node federation scores each connection with GroupSybilRank-style graph analysis → humans clearing the threshold get verified and sponsored into apps like Gitcoin, feeding trust back into the graph. Edit the parameters and watch how attacks and thresholds change the outcome.
New signups 1.4/s connecting Social graph pseudonymous connections Node federation GroupSybilRank, cutoff 60 Rejected Sybils 0 flagged Verified BrightIDs 0 verified Sponsorship (IDChain) 0 sponsored Apps Gitcoin · CLR.fund · Unitap
Signups attempted
0
Verified humans
0
Sybils rejected
0
Apps sponsored
0
Graph trust density
0%
Parameters — edit me
1.4/s
15%
60
1.0×
70%
Controls

Illustrative simulation. Defaults mirror BrightID's documented mechanism (pseudonymous social-graph connections, GroupSybilRank-style node scoring, a verification threshold, sponsorship into apps via IDChain), but signup timing, scores, and outcomes are randomized for visualization — not live onchain data. The "trigger collusion attack" button illustrates the documented weakness of graph-only Sybil resistance to fabricated cliques, it is not a real exploit. Part of The Onchain Experiment Atlas.