Litigation Toolkit

CFAA Evidentiary Checklist for AI Training Data Disputes

Use this checklist to align technical discovery with the statutory elements of 18 U.S.C. § 1030 in matters involving unauthorized harvesting or misuse of proprietary datasets in AI training pipelines.1

Prima Facie Element Alignment

Element

  • Protected computer access
  • Without authorization or exceeding authorization
  • Intentional acquisition of information
  • Loss exceeding $5,000 aggregated over 1 year

Evidence Packet

  • Server access logs, API analytics, and credential audits mapped to defendant identifiers
  • Policy documents, data use agreements, or robots.txt logs capturing scope of authorized activity2
  • Dataset manifests, ingestion scripts, and replication notebooks showing copied records
  • Forensic accounting of remediation costs, incident response hours, and business interruption

Discovery Checklist

  1. Preservation Protocol. Issue litigation holds covering web server logs, IAM audit trails, dataset storage buckets, and cloud billing records. Capture hash authenticators for ingested corpora to maintain integrity.3
  2. Access Vector Analysis. Reconstruct credential use and bypass techniques (e.g., headless browsers, API impersonation, Tor routing) by correlating log anomalies with defendant-controlled infrastructure.5
  3. Dataset Corroboration. Compare the suspect AI training snapshot to the plaintiff corpus via shingling, MinHash, and membership inference testing to document substantial overlap with quantified confidence bounds.
  4. Loss Model Development. Aggregate expert time, breach response tooling, and contract remediation spend. Itemize lost licensing opportunities and system downtime to satisfy the statutory $5,000 threshold.6
  5. Injunctive Relief Support. Document ongoing risk by demonstrating model retraining cadence, automated scraping infrastructure, or expansion into adjacent datasets that threaten continuing harm.47
  6. Expert Declaration Checklist. Prepare sworn testimony covering network forensics, dataset alignment methodology, and economic damages, with appendices that map each factual conclusion to underlying exhibits.

Production Roadmap

Week 0–1

Collect system logs, preserve dataset snapshots, and execute crawl artifacts export. Align privilege review and clawback agreements.

Week 2–3

Run dataset inference probes, consolidate model disclosure requests, and issue Rule 26(f) plan integrating technical discovery milestones.

Week 4+

Finalize damages schedule, draft CFAA-focused deposition outlines, and prepare preliminary injunction briefing if ongoing scraping persists.