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Get Token Risk Assessment
Evaluates up to 17 independent risk factors across multiple categories to identify potential threats, vulnerabilities, and suspicious attributes in tokens. See Understanding Risk Scores for general methodology. Key features:
  • Multi-factor analysis across 17 distinct risk dimensions
  • Real-time assessment with typical response times under 500ms
  • Graceful degradation when some data sources are unavailable
  • Human-readable explanations for each risk factor
Currently supports Solana. Ethereum support is in development. Base, Arbitrum, and Polygon are on the roadmap.

Parameters


Response Schema

Top-Level Fields

Scoring System

Each risk factor scores: LOW = 0 points, MEDIUM = 1 point, HIGH = 2 points. Risk percentage = (total_score / max_possible_score) × 100 Custom threshold configuration is available for enterprise clients, contact info@range.org.

Risk Factors

The API evaluates up to 17 risk factors across 5 categories. Not all factors may be assessed for every token due to data availability.
Circulating Supply Ratio: Detects dilution risk from centralized mint authority control. LOW: >95% circulating, MEDIUM: 80–95%, HIGH: <80%.Freeze Authority: Identifies trading restriction risk. Freeze authority allows token accounts to be frozen, preventing trading. HIGH: present, LOW: absent/disabled.Mint Authority: Assesses supply inflation risk. Active mint authority enables unlimited token creation. HIGH: present, LOW: absent/disabled.
Market Capitalization: Smaller caps are more susceptible to manipulation. HIGH: <1M,MEDIUM:1M, MEDIUM: 1M–100M,LOW:100M, LOW: \>100M.Token Verification: Unverified tokens lack institutional due diligence. HIGH: unverified, LOW: verified.Liquidity: Low liquidity can trap holders. HIGH: <10K,MEDIUM:10K, MEDIUM: 10K–100K,LOW:100K, LOW: \>100K.Holder Count: Few holders indicate high concentration risk. HIGH: <100, MEDIUM: 100–1000, LOW: >1000.Top Holder Concentration: Extreme concentration enables coordinated dump attacks. HIGH: >90%, MEDIUM: 80–90%, LOW: <80%.
Price Volatility: Extreme swings suggest instability or manipulation. HIGH: >50%, MEDIUM: 20–50%, LOW: <20%.Wash Trading: Detects artificial trading creating false liquidity impressions. HIGH: suspicious in ≥2 timeframes, LOW: normal patterns.Organic Activity: Evaluates authentic demand vs bot-driven trading. HIGH: low organic score, MEDIUM: medium, LOW: high organic score.
Developer Migrations: Frequent team migrations indicate instability. HIGH: ≥5, MEDIUM: 2–4, LOW: <2.Exchange Listings: Major exchanges require due diligence. HIGH: no listings, MEDIUM: <3 or no major, LOW: major exchange listings.Launchpad Platform: Some platforms have higher historical fraud rates. HIGH: high-risk platforms (e.g., pump.fun), LOW: other platforms.Social Media Presence: Team transparency reduces exit scam risk. HIGH: no presence, LOW: active presence.
Token Age: New tokens lack operational track record. HIGH: <7 days, MEDIUM: 7–30 days, LOW: >30 days.Graduation Status: Recent launchpad graduations can create price volatility. MEDIUM: <7 days since graduation, LOW: >7 days or N/A.

Risk Factor Summary


Examples

Low-Risk Token (USDC)

USDC shows LOW overall risk (23.1%) despite having freeze/mint authorities, demonstrating how multiple factors contribute to the final assessment.

Medium-Risk Token (Limited Data)

Tokens with limited data result in fewer assessed factors. The API adjusts the maximum possible score accordingly, but partial assessments should be treated with additional caution.

Errors

Invalid Address Format (422)

Unsupported Network (400)


Best Practices

  • Use the errors array to understand which risk factors were skipped due to data unavailability.
  • Tokens with fewer assessed factors may need additional manual review, a low score based on 3 factors is less reliable than one based on 13.
  • For compliance workflows, combine token risk assessment with the Address Risk Score for the token’s deployer address.
  • Test with known tokens (USDC, USDT, BONK) to understand response patterns before integrating.
Stablecoins:
  • USDC: EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v
  • USDT: Es9vMFrzaCERmJfrF4H2FYD4KCoNkY11McCe8BenwNYB
Infrastructure:
  • Wrapped SOL: So11111111111111111111111111111111111111112
  • JUP: JUPyiwrYJFskUPiHa7hkeR8VUtAeFoSYbKedZNsDvCN
  • Pyth: HZ1JovNiVvGrGNiiYvEozEVgZ58xaU3RKwX8eACQBCt3
Meme Tokens:
  • BONK: DezXAZ8z7PnrnRJjz3wXBoRgixCa6xjnB7YaB1pPB263
  • WIF: EKpQGSJtjMFqKZ9KQanSqYXRcF8fBopzLHYxdM65zcjm
  • POPCAT: 7GCihgDB8fe6KNjn2MYtkzZcRjQy3t9GHdC8uHYmW2hr

Authorizations

X-API-KEY
string
header
required

Authorization method required to allow user to access the api endpoints.

Query Parameters

asset_address
string
required

Asset identifier (chain-agnostic). Currently only Solana token mint (base58, 32–44 chars) is supported.

Example:

"So11111111111111111111111111111111111111112"

network
enum<string>
required

Blockchain network for token risk (only solana supported)

Available options:
solana
Example:

"solana"

Response

200 - application/json

Token risk assessment with detailed factors and scoring

token_info
object
required

Basic token identification details

overall_assessment
object
required

Overall risk assessment aggregation

summary
object
required

Summary counts of risk factor severity levels

risk_factors
object
required

Map of risk factor key to its detailed assessment

processing_time_ms
number
required

Processing time in milliseconds for the assessment

Example:

154

errors
string[]
required

List of non-fatal errors encountered while computing the assessment

Last modified on June 17, 2026