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edycutjong/README.md

Edy Cu

I build the safety layer that lets AI agents move real money: spend caps, human sign-off, approval revocation and prompt-injection defense. My work is mostly MCP servers and on-chain tooling in TypeScript and Python.

Jakarta, Indonesia (UTC+7) · Open to remote, async-first · edy.cu@live.com · LinkedIn · edycu.dev


Proof

🏆 Track winner, QwenCloud Hackathon 2026 Tarmac: Track 3, Agent Society. US$7,000 cash prize. Submission
🔀 Merged upstream KeeperHub PR #2277: trace-method availability probe with 38 tests. Two review rounds; shipped in v3.5.0
🥈 2nd place, Nansen CLI Build Challenge (week 2) NansenTerm, one of 4 entries, one in every week of the challenge (all submissions)
📦 In use bagos-mcp-server on npm, published with provenance and listed in the MCP Registry

Selected work

BagOS: an MCP server that lets an AI agent trade on Solana without being able to drain the wallet. TypeScript, MCP SDK, @solana/web3.js.

  • Every write goes simulate → preview → single-use confirmation → sign → confirm, with per-transaction and per-session SOL caps.
  • I found a fake-success bug in v1, deprecated that release, documented it in the 2.0.0 changelog, and added CI gates that make that class of bug unshippable.
  • An outside adversarial review found a critical wallet-drain: a cloned repo's .env could redirect sign-in, and the sign-in step would sign a transaction. I fixed it in a private fork, shipped 3.0.0, deprecated every affected version on npm, and published GHSA-g679-3wq7-mh3m.
  • I made the session cap safe under concurrent calls and fail closed when a trade's outcome is unknown (postmortem).
  • 407 tests at 100% line and branch coverage. CodeQL, gitleaks, SLSA provenance on every release.

Tarmac: a group of agents that rebooks passengers after flight disruptions, using sealed-bid seat allocation and a hash-chained audit log that can be re-verified byte for byte in the cloud. Python, Qwen, Alibaba Cloud Function Compute. Hackathon track winner.

revoker: threat rules that revoke dangerous token approvals on agent, keeper and relayer wallets before a drain contract can use them. Demonstrated on chain through KeeperHub; built for the Agents Onchain hackathon.

aegis: a multi-agent support engine (FastAPI, LangGraph) that investigates through SQL and docs, proposes actions, and stops for human approval before anything destructive.

antigen: finds and defuses prompt-injection payloads in a DataHub metadata graph, including invisible-Unicode variants, and maps the blast radius through lineage.

How I work

  • I ship with AI coding agents, and I verify what they write. Every claim in a README has to match the code; I've published commits titled "correct the claims an audit disproved". Tests are named after the defects they prevent.
  • I publish failures. I write postmortems for my own bugs, including ones nobody else reported.
  • Conventional commits, release automation, and security scanning on every repo I keep.

Stack: TypeScript, Python, SQL · MCP, Node.js, FastAPI, Next.js, PostgreSQL · Solana, EVM (Foundry) · GitHub Actions, npm/PyPI trusted publishing, Docker

Pinned Loading

  1. BagOS BagOS Public

    🚦 MCP server for Bags on Solana. Every AI-initiated spend is token-gated, SOL-capped, and requires a single-use confirmation before anything is signed.

    TypeScript 1 1

  2. tarmac tarmac Public

    ✈️ Agent society for flight-disruption rebooking: sealed-bid negotiation, mediator, Ed25519-signed rulings · Qwen Cloud hackathon (Track 3)

    Python 3 1

  3. revoker revoker Public

    🛡️ Revokes dangerous token approvals through KeeperHub in 13.47s median — Agents Onchain finalist, top 10 of 190

    TypeScript 1

  4. gavel gavel Public

    👨‍⚖️ Executes Safe multisig transactions that reached their signature threshold but were never executed — from a wallet that owns nothing on the Safe. Built on KeeperHub.

    JavaScript

  5. aegis aegis Public

    ⛊ Multi-agent support engine (LangGraph) that investigates tickets against Postgres and pauses for human approval before any action. Evals: 99.2% pass over 120 runs, 0 safety violations. Live demo ↓

    Python 1

  6. whichone whichone Public

    🟢 Type a ticker. Fourteen tokens share the name — Nansen labels decide which one is real. One green card, deterministic score, full provenance.

    TypeScript