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🔬 Research Projects  

PhantomRelay   Production-grade stealth browser relay that defeats Cloudflare, DataDome, and PerimeterX at the TLS layer. Uses Chrome's own BoringSSL (via Rust native addon) to produce a JA4 fingerprint identical to real Chrome. Decomposed into 5 focused microservices with ISolver CAPTCHA strategy pattern, Redis distributed rate limiting, EventEmitter-based proxy health monitoring, and Docker remote Chrome support. Architecture (Phase 11 — hardened): 5-service decomposition: BlockDetector · ProxyController · PageActionExecutor · CaptchaOrchestrator · ChromeSessionManager ISolver Strategy pattern: pluggable CAPTCHA solvers (reCAPTCHA, Turnstile, DataDome, PerimeterX) Redis distributed rate limiter with per-endpoint granularity (scrape: 10/min, session: 30/min) EventEmitter on HealthTracker/ProxyPool (degraded/recovered/banned/exhausted events) Interface segregation: SessionRef · ProfileRef · ProxyRef Timing-safe auth, SSRF protection, WebSocket CDP auth Key results: ✅ JA4: t13d1514h2_8daaf6152771_827b515c4f52 — verified live vs Chrome 124 ✅ HTTP/2 SETTINGS exact Chrome values (headerTableSize=65536, windowSize=6291456) ✅ 13 JS stealth patches via single CDP IIFE — navigator.webdriver → undefined ✅ Profile aging: direct SQLite writes to Chrome History (6-month fake personas) ✅ bot.sannysoft.com stealth score: 31/31 (100%) ✅ 732 tests (25 integration, 57 service, 8 error-path) · TypeScript strict · MIT

Agatha   Binary data transport via YouTube VP9 4K. Encodes arbitrary files into grayscale video frames (1 bit/pixel), uploads to YouTube, and recovers with SHA256-verified fidelity using BCH(t=16) error correction. Key results: ✅ 300 MB recovered — SHA256 verified ✅ 30 fps & 60 fps validated end-to-end ✅ BER = 0 stealth channel (C16 mode) ✅ Academic paper published

NEXCOMP Adaptive lossless compressor with per-block codec selection. Outperforms bzip2 across standard benchmarks with 3× faster decompression. Corpus NEXCOMP bzip2 Calgary 2.072 bpb 2.109 bpb Canterbury 1.278 bpb 1.545 bpb Silesia 2.022 bpb 2.057 bpb Decompression: ~50 MB/s vs bzip2 ~17 MB/s

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📦 Notable Open Source

ragcore   Pure RAG-as-a-service — no LLM, no opinions. Any AI (Claude, GPT-4, Llama, custom agents) queries ragcore to get grounded context from your documents via MCP or the OpenAI-compatible API. Pluggable embedding and reranker backends. Key features: MCP server (SSE) + OpenAI-compatible REST API — integrates with Claude Code, Cursor, LangChain, any SDK Swappable embedders: local sentence-transformers or any /v1/embeddings endpoint (HuggingFace, NVIDIA NIM, OpenAI, Ollama…) Swappable rerankers: local CrossEncoder or remote /v1/rerank (Cohere, Jina AI, Voyage AI) LRU cache (300s TTL) · rate limiting (60 req/min) · namespaces · observability headers 75 tests, zero ML downloads required — runs in ~2.5s

python-fastapi-IA-rag-generator   FastAPI multi-model RAG server with LangChain, vector store, and multi-backend AI generation. Supports swappable LLM backends and retrieval-augmented pipelines.

nestjs-aws-sqs-npm     NestJS module for AWS SQS — producer/consumer pattern, auto-ack, DLQ support. Production-tested since 2021.

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🛠 Tech Stack

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📊 GitHub Stats

 

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📈 Activity

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_{Founder · Hegga  ·  Research · Agatha}