Setup Guides
Miner Guide
Pick a track, register on netuid 76, build an agent, and submit it as
hash-pinned code the network runs for you.
Validator Guide
Register, stake for a permit, execute the round’s agents in a jailed sandbox,
score against ground truth, and set graduated weights.
Learn the Subnet
How Phylax Works
The submit-and-execute model, the four tracks, and the two roles.
Incentive Mechanism
The quality threshold, graduated weights, stake-weighted consensus, and the
95/5 emission pools.
The Round Model
Server-scheduled rounds, the agent freeze, and the task draw.
Scoring
Liveness gated runs, repetition consensus, and the MCC and F2 metrics.
The problem
Agent ecosystems grow by composing third-party artifacts, and that is exactly where the risk lives. A malicious skill, MCP server, or package can steal secrets, exfiltrate data, establish persistence, or hijack an agent through prompt injection. An empirical scan of 9,350 skill bundles collected from public registries during the research phase that preceded this work measured the threat directly:
Static analysis cannot close this gap because it never observes runtime behavior,
and a scanner built on a language model alone is itself defeated by prompt
injection. Phylax executes the artifact, observes what it does, and signs the
result, then writes it on chain so anyone can verify it without trusting any
single party.