Reading risk scores

Every analysis produces a single risk_score from 0–100. It's a weighted, normalized blend of independent risk dimensions — each scored 0–100 on its own, then combined. Higher means riskier.

Risk levels

The numeric score maps to a risk_level and a recommendation:

ScoreLevelTypical recommendation
0–25LOWSAFE — appears legitimate
26–50MEDIUMCAUTION — investigate further
51–75HIGHAVOID — multiple red flags
76–100CRITICALAVOID — strong scam indicators

The dimensions

The engine evaluates up to twelve independent dimensions, each scored 0–100. Their relative influence is tuned and proprietary; the categories are:

DimensionWhat it detects
Owner privilegesMint/freeze authority, pause, blacklist, balance-modifying admin functions.
Holder concentrationHow tightly supply is held across the largest wallets.
LiquidityPool depth, lock status, lock duration, pairing.
Ownership transfersSuspicious owner changes, transfers to fresh wallets.
Contract verificationVerified source, audit status, honeypot patterns.
Trading patternsVolume/price anomalies vs. historical behavior, wash trading.
Pump.fun signalsLaunchpad-specific risk signals (Solana).
SupplySupply structure and inflation potential.
Relaunch riskCopycats / repeated-deployer patterns.
Proxy riskUpgradeable proxies and their centralization risk.
Gas anomaliesUnusual transfer-gas behavior (a honeypot tell).
Scam connectionsLinks to known scam addresses.

How scores combine

Each dimension yields a 0–100 sub-score. The overall score is a weighted, normalized blend of the dimensions that could be evaluated for a given token — so a missing data source doesn't unfairly skew the result. The exact weighting is proprietary and tuned against real-world outcomes.

Confidence & coverage

Responses include a confidence value (0.0–1.0). When too few core dimensions can be evaluated, confidence drops and the recommendation leans toward CAUTION. Treat low-confidence results as "insufficient data," not "safe."

A score is a risk signal, not financial advice or a guarantee. Always do your own research before interacting with any token.

Next

Data sources Where the signals come from. Scam patterns The behaviors behind the flags.