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Forensik Bytecode Clone Provenance Analyzer
x402
Forensik Bytecode Clone Provenance Analyzer is a paid API for AI agents from forensik.halowerk.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-11-02).
Analyzes caller-supplied bytecode evidence to classify smart contract clone provenance, confidence thresholds, and missing signal gaps without querying any blockchain directly.
Price / call$0.001
Success—
StatusUnknown
How this service works
Bytecode Clone Provenance analyses only the evidence supplied by the caller. It does not claim to query a chain, identify a legal status or replace an independent audit. Missing signals lower confidence and are listed explicitly; every classification includes the exact thresholds used.
Output
Returns a clone provenance classification for the subject (e.g., confirmed clone, likely clone, inconclusive, original), a confidence score with the exact thresholds applied, a list of any missing or low-signal metrics that reduced confidence, and the caller-supplied context labels echoed back for correlation.
Example use cases
DeFi protocol fork detection
“I want to assess clone provenance for the contract at 0xDEFi456 — my evidence shows unmatched_bytecode_pct of 12, unknown_deployer as true, and metadata_divergence_count of 5, timestamped 2024-10-15T08:30:00Z from Etherscan. Tell me the classification and which signals are missing.”
Smart contract audit pre-screening
“Before we audit protocol 'VaultX', can you run a bytecode clone provenance check? Evidence: unmatched_bytecode_pct is 4.2 from our internal scanner at 2024-12-01T09:00:00Z, unknown_deployer is false, and metadata_divergence_count is 1. Flag any low-confidence gaps.”
Unknown deployer risk triage
“We spotted a new contract deploy from an unrecognized address — subject is tx hash 0xTXhash789. Evidence: unknown_deployer true at 2024-11-20T15:45:00Z, unmatched_bytecode_pct 65.0. I need the clone provenance classification and exact thresholds used, and strict mode off so partial evidence is accepted.”
Technical details
Endpoint
POSThttps://forensik.halowerk.com/v1/bytecode-clone-provenance?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected bytecode forensic signals (unmatched bytecode percentage, unknown deployer status, metadata divergence count) for a smart contract and need a structured provenance classification with explicit confidence thresholds — especially when you cannot or do not want the service to perform live chain queries. It is ideal for offline audit pipelines, pre-screening workflows, or integrating forensic scoring into a larger risk assessment system. Prefer sibling endpoints (Dusting Attack Monitor, Address Poisoning Detector) for those specific threat categories instead.
Side effects
- Missing required evidence items returns an error or low-confidence result when strict mode is enabled
- Unrecognized metric enum values are rejected with a validation error
- Evidence array with no items fails schema validation (minItems:1)
- Subject string exceeding 256 characters is rejected
- Stale or conflicting timestamps across repeated metrics may reduce classification confidence
- Calling with strict:true but omitting any documented metric causes the request to be rejected outright
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| strict | boolean | Reject unless all documented metrics are supplied. |
| context | object | Optional non-secret labels returned unchanged for correlation. |
| subject | string | Address, transaction, protocol, asset, proposal or other subject being assessed. |
| evidence | array | Caller-supplied observations. Repeated metrics form a time series; the newest timestamp is assessed. |
Tags
x402
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