VECTOR384 / dossierVECTOR 384 — Systems Engineering PortfolioRudra Mahapatro — Systems EngineerRust · C++ · Offensive Security · Trading SystemsStatus: available

// under pressure

I architect systemsthat don't break.

Rust. C++. Zero-copy. I build the tools that other engineers depend on when it actually matters.

fig. 01 — flashaudit run · M1 Pro, 10 cores
$flashaudit scan --repo enterprise-monorepo
Scanning 847,000 files...
Found 23 exposed secrets in 0.4s
SARIF report exported to ./audit.sarif
$uptime
3+ years · 160+ commits · shipping since day one
$
Rudra Mahapatro — Systems Engineer
subject:
r. mahapatro

If a number is on this page, it was measured.

peak throughput0Kfiles scanned in 0.4s · FlashAudit, enterprise monorepo
speedup delivered0×vs. Gitleaks 8.18 · same corpus, same rules
minimum latency<0msp50 across hot paths · BioStream, ~3K events/s
methodologyhyperfine · N=10 warm runs · /usr/bin/time -lreproduce → /benchmarks

The Record.

§ A — systems & security · 5 files

FlashAudit Core

Enterprise Secret Scanner in Rust

incident — A client's Gitleaks pre-commit hook took 4 minutes on their monorepo. Engineers disabled it. Secrets shipped.

Rust · Rayon · Memory-Mapped I/O · SARIF

Enterprise-grade secret scanner built in Rust with zero-copy I/O, memory-mapped files, and Rayon work-stealing across every core. Outputs SARIF so it drops into existing CI pipelines without rewiring dashboards. Built because the existing scanners couldn't keep up with real repo sizes.

Speed847K files in 0.4s — roughly 10x Gitleaks on the same corpus.
ArchitectureZero-copy I/O, memory-mapped files, Rayon parallel scan.
open case file →
fig. — flashaudit vs. gitleaks 8.18
Files scannedenterprise monorepo corpus847,000
Wall-clock timeM1 Pro, 10 cores0.4s
Speedup vs Gitleaks 8.18same corpus, same rules~10x
full methodology → /benchmarks

Proxy Server

Native Windows Firewall Proxy

incident — A staging box kept getting probed with SQLi and path-traversal payloads. Userland proxies added 30ms. Native Win32 at the packet level was the only path under budget.

C (ANSI/Win32) · Raw Sockets

A multi-threaded HTTP proxy written in pure C — no frameworks, no dependencies. Inspects every packet for SQL injection and path traversal patterns, then auto-bans offending IPs. Built on raw Win32 threads because the problem didn't need abstractions, it needed speed.

Rate LimitAuto-bans IPs exceeding 50 requests in 15 seconds.
FootprintZero external frameworks — pure Win32 threads and raw sockets.

CredGuard

Identity Security Platform

incident — Paste sites and combo lists leak credentials daily. Enterprise SOCs monitor for it; individuals get notified after the fraud hits.

Python · Streamlit · PostgreSQL · Stripe

A monetized personal SOC that monitors digital identities for credential leaks across dark web dumps and public repos. Integrated Stripe for billing from day one — this isn't a demo, it's a product with paying users and audit-grade PDF reporting.

MonetizationStripe billing, rate-limiting, and audit-grade PDF reporting.
DetectionRisk score (0-100) via anomaly detection on breach data.
03.04source: shipping soon

DataCenter Manager

Concurrent Resource Orchestrator

incident — Every tutorial on Pthreads uses counters and toy queues. Real resource contention — thread pools, condition variables, lock ordering — only shows up when you build it.

C++20 · CMake · Pthreads

Multi-threaded data center simulation built on raw Pthreads. Mutex-locked resource pools, condition variable signaling, and a custom thread pool. The kind of systems programming that doesn't show up in tutorials but runs under every cloud provider.

ConcurrencyPthreads with mutex-locked pools and condition variable signaling.
ArchitectureCustom thread pool with work-stealing scheduler.
03.05source: shipping soon

StegoVault

Steganographic Encryption Tool

incident — Encrypted blobs announce themselves on disk and in transit. Sometimes the threat model requires that the data isn't visibly there at all.

Python · Flask · AES-256 · LSB Steganography

Hides AES-256 encrypted payloads inside ordinary images using LSB steganography. The output passes visual inspection and steganalysis tools. Built for scenarios where the existence of the data itself is sensitive — not just its contents.

EvasionOutput survives steganalysis detection tools.
EncryptionAES-256 payload encryption before steganographic embedding.

§ B — fintech & trading · 3 files

03.06restricted — case study only

NSE Trading Engine

SEBI-Compliant Algorithmic Trading

incident — Algo-Bot kept missing SEBI circuit-breaker timing and retail APIs throttled mid-session. A production rewrite was the only way to trade inside compliance windows.

Electron · React 19 · FastAPI · Angel One API

Full-stack trading platform for NSE markets with a desktop-native Electron frontend and FastAPI backend. SEBI-compliant order execution, real-time P&L tracking, and a kill switch that actually works. This is the system that superseded Algo-Bot — same problem, production-grade solution.

ComplianceSEBI-compliant execution with automated circuit breakers.
LatencySub-second order placement via Angel One SmartAPI.
open case file →
03.07source: shipping soon

GlassVault

Encrypted Personal Finance

incident — Every finance app I audited shipped plaintext SQLite under the hood, cloud-first by default. There's no personal-finance tool that trusts you to own your own data.

Flutter/Dart · SQLCipher · Riverpod · CRDT Sync

A personal finance tracker where every byte is encrypted at rest with SQLCipher. CRDT-based sync means your data stays consistent across devices without a central server seeing it. Built in Flutter because finance apps should run everywhere.

SecuritySQLCipher AES-256 encryption — data encrypted at rest, always.
SyncCRDT-based conflict resolution for offline-first multi-device sync.
03.08source: shipping soon

Algo-Bot

Early Trading Architecture

incident — Manual entries kept missing the fills I was backtesting. Automating it surfaced every hole in the plan — this is where I learned what retail APIs can't do.

Python · Upstox API · Pandas

The first iteration of my trading engine — event-driven execution for NSE with automated risk-management kill switches. Taught me what retail APIs can and can't do, and directly led to the NSE Trading Engine rewrite with proper infrastructure.

EvolutionSuperseded by NSE Trading Engine — lessons from this built that.
Risk MgmtAutomated kill switches for position limits and drawdown.

§ C — full-stack products · 3 files

BioStream ML

Real-Time Surgical Telemetry Engine

incident — In OR telemetry, deterioration is caught by eye — minutes after it starts. Monitors beep on threshold, not trend. That window is where patients are lost.

Python · Redis Streams · Docker · Isolation Forest

A fault-tolerant pipeline that processes heart rate and SpO2 data in real time, flagging clinical deterioration before a human would notice. Redis Streams for exactly-once delivery, Isolation Forest for anomaly detection. Zero data loss by design.

Throughput~3,000 events/second with sub-5ms latency.
ReliabilityZero data loss via Redis Streams idempotency.
DetectionReal-time clinical deterioration flagging with Isolation Forest.
open case file →
03.10source: shipping soon

Staleness Scanner

Dependency Freshness Monitor

incident — Every team I've worked with learned about a stale dependency when a CVE landed on a Friday. Dependabot spams; nobody triages. Staleness needs to be visible before it's urgent.

Next.js · FastAPI · PostgreSQL · Redis · arq

A full-stack tool that scans repos on a schedule, scores dependency freshness, and flags staleness before it becomes a security incident. Background workers via arq, PostgreSQL for persistence, Redis for caching. Built so engineering leads can see the health of every repo at a glance.

PipelineBackground scanning via arq workers with Redis-backed queue.
VisibilityPer-repo freshness scores with historical trend tracking.

Warp P2P

Peer-to-Peer File Transfer

incident — Every large-file transfer tool still round-trips through somebody else's server. You pay in upload time and in who-sees-your-file. Browsers ship WebRTC — we shouldn't need a middleman.

TypeScript · WebRTC · Node.js

Direct browser-to-browser file transfer using WebRTC data channels. No upload, no server in the middle, no file size limits. The connection is peer-to-peer — your file goes from your machine to theirs, and nobody else sees it.

TransferDirect P2P via WebRTC — no intermediate server storage.
PrivacyFiles never touch a third-party server.

Most engineers build for the happy path. I build for the moment everything goes wrong.

identity.conf
name
Rudra Mahapatro
handle
VECTOR384
status
available
location
India · working globally
clearance
systems · security · trading
§ 1 — the why

Production goes down. Everyone scrambles. Root cause? A hardcoded secret. A service that buckles at 2x load. I kept seeing it — teams shipping tools that passed demos but crumbled under real traffic. I decided I’d rather build the tools that survive the 3 AM incident than the ones that cause it.

§ 2 — the path

Started with Python. Hit the ceiling fast — try scanning a million files when your runtime has a GIL. So I picked up C++, then Rust. Not from tutorials — from shipping real systems and debugging real failures. Offensive security taught me how things actually break. Algorithmic trading taught me that 50ms of latency is the difference between profit and loss. Every skill I picked up, I picked up because I needed it to solve a problem nothing else could.

stack inventoryby depth
Rustcore
C / C++core
Pythoncore
Next.jscore
Metasploitcore
Burp Suitecore
Goprof
PostgreSQLprof
Dockerprof
Redisprof
LangChainprof
TensorFlowfam

fig. 02 — stack inventory, by depth

§ 3 — the mission

FlashAudit scans 847K files in under a second — Gitleaks takes minutes. My trading engine handles SEBI-compliant execution with a kill switch that works. My steganography tool hides encrypted payloads in images so well that steganalysis tools can’t find them. I don’t build proof-of-concepts. I build things that work under pressure, and I can prove it.

Engagement.

Your Python service is slow? I've rewritten hot paths in Rust that went from minutes to milliseconds. I built FlashAudit this way — zero-copy I/O, memory-mapped files, parallel execution. The result was 10x faster than Gitleaks on the same workload.

deliverables

  • Profiling to find the real hot path
  • Rust/C++ rewrite of the critical section
  • Zero-copy and memory-mapped I/O where it counts
  • Benchmarks proving the improvement

I built FlashAudit because existing secret scanners were too slow for enterprise repos. I can do the same for your pipeline — scanning that runs in CI, catches credentials before they ship, and doesn't slow down your deploys.

deliverables

    I've shipped full-stack products end-to-end — trading platforms, SaaS tools, finance apps. Database to deploy, with auth, payments, and monitoring that works. I build for the engineer who inherits the codebase after me.

    deliverables

      I don’t build software that works in demos. I build software that works at 3 AM when the on-call engineer is staring at a dashboard wondering what went wrong.

      — operating principle, v384