The world's first universal scarcity scoring engine. Score fraud, vulnerabilities, AI quality, credentials, assets, and any data point across any industry — in milliseconds.
Three steps. Any data. Instant scarcity intelligence.
POST any transaction, vulnerability, credential, or asset data to our API endpoint
Our engine computes Information (Shannon entropy) and Cost (Landauer verification) instantly
Get risk levels, recommended actions, bounty estimates, and efficiency scores in real-time
S = I × C scores anything with information content and verification cost. Every letter of the alphabet.
Score crop yield scarcity, seed IP novelty, and soil data verification. Predict shortages before they hit markets.
Score every transaction for fraud in real-time. 9 signal inputs, instant risk classification, recommended actions. Replace expensive human review.
Score vulnerabilities with math, not opinion. Replaces CVSS. Bounty estimates calibrated to Zerodium ($0-$2.5M).
Score threat actors, attack vectors, and intelligence reports for novelty and verification difficulty. Nation-state grade.
Score energy supply scarcity, outage risk, and grid vulnerability. Predict blackouts before they cascade.
Real-time payment fraud scoring. Velocity analysis, geo-anomaly detection, device fingerprinting — all in <50ms.
Score in-game item scarcity, NFT rarity, and digital collectible verification. True mathematical rarity, not hype.
Score medical claims, treatment efficacy, diagnostic accuracy. Clinical trial novelty vs replication cost.
Score risk with information-theoretic precision. Event surprisal as I, claim verification as C. Better than actuarial tables.
Score evidence authenticity, witness reliability, and legal precedent novelty. Verification cost maps to litigation complexity.
Score certifications, degrees, and skills for true scarcity. Pass rates, holder counts, time investment — one signal score.
Score components for disruption risk. Single-source dependency, geographic concentration, substitution difficulty.
Score defect rarity, production anomalies, and quality verification cost. Catch the defects that matter most.
Score mineral deposits, extraction difficulty, and geological verification cost. Real thermodynamic scarcity of physical resources.
Score talent scarcity in any skill domain. Combine credential rarity with market demand for true hiring signal.
Score compound novelty, clinical trial replication cost, and regulatory verification burden. Faster drug scoring.
Score AI responses by information density vs compute cost. Lexical diversity, efficiency ratios, true value per token.
Score location scarcity, zoning rarity, and property verification cost. Beyond comps — true information-theoretic value.
Score papers for originality and replication cost. Citation novelty, methodology uniqueness, finding surprise factor.
Score spectrum scarcity, bandwidth allocation efficiency, and network verification cost. The physics of connectivity.
Score grid capacity, water treatment, infrastructure age — verify critical systems before they fail.
Score startup deal scarcity: team uniqueness, market timing, tech novelty vs due diligence cost. Quantify deal quality.
Score water scarcity, environmental data quality, and pollution verification cost. The most fundamental resource.
Score token TRUE scarcity beyond market cap. Hash difficulty, network uniqueness, protocol novelty, mining cost.
Score crop insurance claims, yield prediction accuracy, and agricultural commodity verification.
Score zero-day exploits for bounty pricing. Novelty, impact, complexity, reproduction difficulty — Zerodium-calibrated.
| SIE-Score (Kinetigor) | Scale AI | CVSS | Manual Review | |
|---|---|---|---|---|
| Speed | <50ms per score | Hours to days | Minutes (manual) | Hours to weeks |
| Cost per evaluation | <$0.001 | $15-25/hr human | Free but slow | $50-200/hr analyst |
| Objectivity | Mathematical | Human bias | Subjective inputs | High variance |
| Cross-domain | Universal (10+ industries) | AI data only | Vulnerabilities only | Domain-specific |
| Scalability | Infinite (serverless) | Limited by headcount | N/A | Linear with staff |
| Theoretical basis | Shannon + Landauer | Human consensus | Ad hoc formula | Expert opinion |
A novel mathematical framework unifying Claude Shannon's information theory (1948) with Rolf Landauer's thermodynamic cost principle (1961). No prior art exists.
curl -X POST https://bountywarz.vercel.app/api/sie-score \
-H "Content-Type: application/json" \
-H "X-Garden-Key: YOUR_API_KEY" \
-d '{"type":"fraud_check","data":{"amount_usd":5000,"velocity":8,"geo_distance_km":8000,"device_fingerprint_match":false}}'All requests require an API key via the X-Garden-Key header. Get your key below.
{
"type": "fraud_check", // scoring type (see below)
"data": { ... } // type-specific parameters
}Score any financial transaction for fraud risk. Returns risk level and recommended action in under 50ms.
| Parameter | Type | Default | Description |
|---|---|---|---|
| amount_usd | number | 0 | Transaction amount in USD |
| velocity | number | 1 | Transactions per hour from this source |
| geo_distance_km | number | 0 | Distance from last known location |
| device_fingerprint_match | boolean | true | Does device match known profile |
| time_anomaly | boolean | false | Unusual time for this user |
| merchant_risk | 1-10 | 3 | Merchant category risk level |
| account_age_days | number | 365 | Account age in days |
| failed_attempts | number | 0 | Recent failed auth attempts |
| cross_border | boolean | false | International transaction |
Response includes:
risk_level: LOW MODERATE ELEVATED HIGH CRITICALrecommended_action: ALLOW / FLAG / REVIEW / CHALLENGE / BLOCKScore vulnerabilities with bounty estimation. Replaces CVSS with information-theoretic scoring calibrated to Zerodium ranges.
| Parameter | Type | Default | Description |
|---|---|---|---|
| novelty | 1-10 | 5 | How novel the attack vector is |
| impact | 1-10 | 5 | Damage potential |
| exploit_complexity | 1-10 | 5 | Exploit chain complexity |
| reproducibility | 1-10 | 5 | How hard to reproduce (higher = harder) |
| cwe | string | "unknown" | CWE identifier |
Response includes: bounty_estimate_usd ($0-$2.5M), cvss_equivalent (0-10), percentile
Score AI model outputs by information density vs compute cost. Measure true value per dollar.
| Parameter | Type | Default | Description |
|---|---|---|---|
| model | string | "unknown" | Model identifier (e.g. claude-sonnet-4-6) |
| tokens | number | 500 | Token count |
| response_text | string | "" | The AI response text to analyze |
Response includes: efficiency (I/C ratio), lexical_diversity, total_cost_usd
Score any credential, degree, or certification for true market signal strength.
| Parameter | Type | Default | Description |
|---|---|---|---|
| credential | string | "Unknown" | Credential name |
| years_to_earn | number | 1 | Years to obtain |
| pass_rate | 0-1 | 0.5 | Exam pass rate |
| holders_worldwide | number | 100000 | Total holders globally |
Score any asset using raw information bits and verification cost.
| Parameter | Type | Default | Description |
|---|---|---|---|
| name | string | "Unknown Asset" | Asset name |
| information_bits | number | 1 | Information content (Shannon bits) |
| verification_cost_usd | number | 1 | Cost to verify in USD |
Provide your own I and C values for direct scarcity computation.
| Parameter | Type | Default | Description |
|---|---|---|---|
| I | number | 0 | Information value |
| C | number | 0 | Verification cost |
{
"type": "fraud_check",
"equation": "proprietary formula",
"S": 0.3543, // Scarcity score
"I": 0.688, // Information (Shannon surprisal)
"C": 0.515, // Cost (Landauer verification)
"risk_level": "HIGH",
"recommended_action": "CHALLENGE",
"amount_usd": 5000,
"breakdown": {
"I_components": { "velocity": 0.4, "geo_distance": 0.8, ... },
"C_components": { "amount_at_risk": 0.05, "merchant_risk": 0.3, ... }
},
"interpretation": "HIGH — Strong fraud signals. Require additional verification."
}Select a scoring type and hit Score It to see real results from our live API.
Start free. Scale when you're ready.