TAO $223.74+2.8% 24h
54

Yanez

sn54Security & PrivacyWatch31Strong entry74

No description set on the registered repo.

Emission
1.7
TAO / day · live
Alpha
0.0229
τ · mcap 94.8K
Top-slot payout
0.048
τ per winning epoch · live

Chain-evidence assessment

A transparent heuristic over the signals subtensor storage can prove — not an accusation. Every subscore cites the exact storage map it was computed from. Signals that need metagraph or transfer history are listed below as not modeled.

31
Watch
Emission concentration ×0.5062

Share of live emissions captured by the single top-ranked miner.

Development dormancy ×0.300

Days since the registered repo was last pushed (live GitHub metadata).

Emission status ×0.200

Emissions enabled and flowing on chain.

Assessment

model provenance

Confidence85%
Computed2m ago
Enginetaonets-integrity live-chain v1
Inputssubtensor storage + GitHub pushes
Weights renormalize over the subscores that have data; `confidence` reports how much of the model was assessable. Nothing is filled in with placeholders.

Not modeled

signals we refuse to fake

  • Owner self-miningneeds transfer history
  • Validator oligopolyneeds metagraph
  • Registration captureneeds per-uid history

These arrive when taonets runs its own indexer. Until then this page shows only what the chain can prove — a shorter list, but a true one.

Evidence ledger

every flagged signal, with its chain reference

Top miner holds 55.9% of subnet emissions

SubtensorModule::Emission normalized across 140 earning uids · top-10 hold 98.4% · 2 τ/day at stake.

subscore: emission concentration

Raw inputs

the storage values this assessment was computed from

SubnetTaoInEmission
238394 rao/block
Emission (top-1 share)
55.9%
Emission (top-10 share)
98.4%
SubnetEmissionEnabled
true
FirstEmissionBlockNumber
5,228,683
GitHub pushed_at
21d ago
Active (uids)
18
Burn
0.0005 τ

Cluster classification (Security & Privacy) is derived from the repo's own text — see the GitHub tab. Live state syncs on the worker's schedule; see methodology for the full model.

Integrity · Taonets