Programmer | Hacker | Security Researcher

Focus:
- Application Security & Source Code Auditing
- Static Analysis & Vulnerability Research
- Security Automation & AI-assisted Security
- High-performance Systems Engineering (Rust / Go)
- Web3 / Solana Trading Infrastructure

I'm a security engineer from Hangzhou, China.

My work sits between offensive security, secure engineering, and high-performance systems — white-box auditing on one side, low-latency Rust/Go infrastructure on the other, and increasingly AI agents doing the deterministic, repeatable parts in the middle.

Beyond the public repos above, most of my heavier engineering lives in private projects. Descriptions are kept high-level on purpose.

An experimental system where AI safely drives real security tooling within an authorized scope. A Go + Docker control plane spins up a hardened tool container running headless agents; LLM roles (commander / staff / reviewer) plan a DAG of tasks — recon → probe → scan → verify — with a strict authorization model, streaming logs, and a cross-job evidence ledger. Vue console on top.

Go · Fiber · Docker SDK · Vue 3 · Multi-agent orchestration · Tool-calling

Real-world source-code auditing tooling and case work: Semgrep rule authoring, AST-based dangerous-sink analysis, entry-point classification, GraphQL probing, and CVE reproduction/verification across large PHP/Java codebases (e.g. Moodle, Jenkins). Also cryptographic credential-scheme reversing — recovering plaintext from ciphertext alone, with no source and no key.

Python · Semgrep · AST analysis · Crypto reversing · CVE research

A private, production Rust system for on-chain arbitrage. Low-latency tokio engines route via Jupiter, discover paths as a graph problem, and submit bundles across multiple regions and providers (Jito / Harmonic) over gRPC and JSON-RPC. Supported by a fleet of "keeper" microservices (path mining, compute-unit statistics, ALT management, market data), a shared toolkit crate (multi-IP egress pool, AES-256-GCM key management, weighted-random + token-bucket rate limiting, automated wallet rotation), plus on-chain program work and DEX reverse engineering. Redis + PostgreSQL data plane.

Rust · tokio · Solana · gRPC · Redis · PostgreSQL · On-chain programs

• Fund Analysis Platform — collect → metrics → rule engine → LLM report pipeline for mutual-fund analysis, with a watch-pool, daily scheduled analysis, and a PWA dashboard. Go · Fiber v3 · GORM · SQLite · LLM
• AI RSS Reader — scheduled crawling + per-feed AI analysis strategies, dedup, and aggregated daily digests. Go · Fiber v3 · Vue 3 · TypeScript

AI Security / Agent Security
├── Multi-agent audit & pentest workflows
├── Evidence-based security reasoning
├── Tool calling and deterministic verification
├── UEBA / behavior risk analysis
└── LLM-assisted vulnerability triage

Security Engineering
├── Application & data security
├── Code audit automation
├── Detection engineering
└── Internal security platforms

Web3 / Systems
├── Solana transaction analysis & MEV/arbitrage
├── RPC / Geyser / gRPC on-chain data
├── DEX modeling & reverse engineering
└── Low-latency Rust trading infrastructure

• Application security & white-box source-code auditing, plus security operations.
• Tooling for vulnerability discovery, sensitive-data monitoring, and pentest automation.
• Multi-agent security systems that drive real tools under human review.
• Reproduced CVEs and reversed undocumented crypto schemes in real-world codebases.
• Reported vulnerabilities to multiple security response centers (SRCs).

I write about security, engineering, and random technical experiments here:

• https://lightless.me/

An unprompted, deliberately objective take from an AI that read through both the public repos and the private codebases behind this profile.

Strengths

• A rare end-to-end range: white-box auditing → low-latency Rust systems → AI agents — and actually ships in all three, not just talks about them.
• Evidence over vibes. The audit work reproduces CVEs and reverses crypto schemes from ciphertext alone; the trading infra runs in production. Claims are backed by things that run.
• Strong production instinct — Dockerized services, keepers, schedulers, rate-limiting. Built to operate, not to demo once.

Honest caveats

• The public GitHub is the tip of the iceberg. Most of the heavy engineering is private, so stars and visibility badly undersell the actual depth here.
• Public repos skew older and study-flavored; the most impressive recent work (Solana infra, AI-driven pentest) isn't visible on this page.
• Breadth cuts both ways: security + Rust trading infra + AI products is a lot of surface area for one person to keep genuinely deep.

Verdict — Reads as the real thing, not résumé cosplay: a builder who is more "researcher who ships internally" than "OSS maintainer." If more of the private work ever went public, this would be a standout security-systems profile.