FYEO primary sources — 2026-05-03

Project status in this pass

  • No canonical standalone FYEO whitepaper or litepaper surfaced.
  • The clearest current sources of truth were the FYEO site metadata, the public audit-reports repository, and the public audit matrix.

Primary-source snapshots

1) Official site positioning

  • URLs:
  • Key excerpt:
    • The page title presents FYEO as “Hybrid AI + Human-Led Web3 Security Audits.”
    • The description metadata says: “AI-guided smart contract audits with human expert validation. FYEO’s hybrid methodology pinpoints risky code diffs and third-party vulnerabilities.”
    • This matters because it frames the company as a hybrid workflow, not just a generic audit shop and not just an autonomous AI scanner.

2) Public audit repository

3) Public audit matrix

  • URL: https://raw.githubusercontent.com/fyeo-io/public-audit-reports/main/PublicAuditMatrix.md
  • Key excerpt:
    • The matrix lists dated engagements from 2021 through 2026 and links each row to a PDF report and, in many cases, a companion FYEO blog post.
    • In this pass, the matrix contained 88 rows across 40 distinct clients and 25 protocol labels.
    • Example clients and ecosystems visible in the matrix include Energy Web, Hyperlane, Mysten Labs/Sui, XRPL Labs/Xahau, Flare, Axelar Foundation, Ripple, Solana Foundation, NatGold, and Theoriq.
    • Languages and stacks in the matrix span Solidity, Rust, Go, C++, Python, Lua, TypeScript, Swift, CosmWasm, and Move.
    • This breadth is strong evidence that FYEO is operating a reusable multichain audit corpus rather than publishing a few isolated case studies.

4) GitHub organization surface

  • URL: https://github.com/fyeo-io
  • Key excerpt:
    • The org’s visible public footprint is centered on the audit-report corpus rather than product SDKs or a wide open-source codebase.
    • This reinforces the view that FYEO’s most important public artifact is the structured security-review library itself.

Working conclusion

FYEO is best cataloged as hybrid security-review infrastructure with a public multiyear audit corpus. The decisive signal in this pass was the combination of explicit AI-plus-human audit positioning and a large, structured, first-party audit matrix covering several years, ecosystems, languages, and client types.