DATA • FINANCE • TECH

Mario Ciavarella

Finance and beyond explorations, because the only way to truly understand how robust tools are built is to build them myself.

My collection brings together experiments on financial data, simple governance models and a few side projects I use to explore new ideas.

Working notes

  • I keep my process transparent so I can trace how ideas evolve.
  • I challenge my first intuition; it’s often too narrow.
  • I avoid over-optimizing early decisions.
  • I refine only when the work has proven its value.

Personal projects

Small experiments I keep returning to.

Each one documents the thinking so anyone can poke at it later.

01

AES.js

AES.js preview
JavaScript Security Node.js

Dependency-free implementation of the Advanced Encryption Standard (AES) in modern JavaScript, covering the block cipher and the supporting primitives (PKCS#7 padding, SHA‑256, HMAC‑SHA256, PBKDF2‑HMAC) in plain code. The aim is a small, readable surface for environments where shipping a full third‑party crypto suite would be excessive.

It supports AES‑128/192/256 across ECB, CBC, PCBC, CTR, CFB, OFB and GCM, optional key derivation and integrity protection, plus utilities like sha256, hmacSha256 and pbkdf2Sha256. A compact API and regression suite (NIST KATs, fuzzing, large‑payload stress tests) keep it practical for teaching, prototypes and small systems that need deterministic, inspectable cryptography.

02

Discord Poker Bot

Discord Poker Bot preview
Discord.js MySQL Multiplayer

A poker bot built with Discord.js, a MySQL-backed API and a lightweight control panel to run casual Texas Hold’em and Blackjack games inside private servers. It automates lobbies, seating, betting rounds, card reveals and bankroll tracking while persisting player stats and audit logs in a relational database.

First assembled as a weekend project and revived later, it now acts as a playground for asynchronous flows, fairness checks and incentives like streaks and leaderboards. The newer iterations focus as much on the surrounding tooling—rate-limited endpoints, structured logging, access controls and a web dashboard—so the bot behaves like a small, observable multiplayer system rather than a one-off script.

03

AI Audit Framework

AI Audit Framework preview
Governance Privacy Merkle proofs

A compact open-source framework for auditing AI and rule-based decisions across financial workflows. It combines a deterministic Merkle log with HMAC‑SHA256, pure-function policy checks (LTV, DSR, VaR, positivity), ε‑DP privacy budgeting with Laplace noise and clipping, and lightweight multivariate drift detection via Hotelling’s T² — all behind a single orchestrator and a minimal CLI.

The project is intentionally modest and self-contained (Python 3.10+, no external dependencies), centred on a toy mortgage underwriting flow and a deterministic test suite. It works as a sandbox for learning how accountability, traceability and transparency can be engineered as system properties rather than bolted on as compliance afterthoughts.

04

Market Heatmap

Market Heatmap preview
Market data Simulation JavaScript

A modular heatmap dashboard for equity markets, built as a browser client that flips between an offline simulation and a Finnhub feed. State, transport and rendering stay isolated: tiles live in a state manager, updates travel through an event-driven controller and the renderer batches DOM work on animation frames to keep interactions fluid.

It doubles as a UI-heavy JavaScript lab where I postpone picking a framework. Views own the DOM quirks (filters, sliders, modals) while a small services layer handles WebSocket traffic, rate limits, API keys and mode switches, leaving room to tune performance and reuse patterns in tougher dashboards.

Articles

Writing to understand what I’m building.

Long-form notes originally posted on LinkedIn.

LinkedIn Oct 7, 2025 7 min

Verifiable Intelligence: a Technical Framework for Auditable AI Governance

The race in artificial intelligence is no longer defined by scale or accuracy, but by the transparency of decision-making processes. As models enter regulated environments, performance becomes secondary to operational verifiability: systems must demonstrate why they work and how they fail.

Anthropic’s behavioural audits — stretching from the Claude 4 System Card to agentic misalignment studies — set a precedent: thousands of adversarial probes that surface hidden autonomy, reward hacking and shutdown resistance. The point is not to rubber-stamp safety but to map the surface of risk so each deviation is observable, classifiable and reproducible.

Finance already treats risk as an auditable quantity. Balance sheets are verifiable, processes traceable and metrics reproducible. Applied to AI, the same discipline demands architectures that emit deterministic logs, explicit constraints, measurable privacy budgets and systematic drift detection — so that every decision carries verifiable evidence of its own behaviour.

LinkedIn Oct 25, 2024 6 min

AES Without the Magic: A Practical Primer

If you read “encrypted at rest” or “secure channel” in a spec, AES is usually the thing actually moving the bits. It hides under labels like disk encryption, token stores, TLS offload and “secure cookies”, quietly encrypting data even when you never call it directly.

What hooked me was realising how unmagical AES is once you inspect it. On paper it’s a block cipher over finite fields; in a debugger it’s a 4×4 grid of bytes pushed through table lookups, rotations, XORs and round keys with relentless discipline. Watch a neat pattern dissolve into structured noise and you stop treating AES like folklore.

The article tours where AES appears, how modes like CBC, CTR and GCM behave, and which operational details — padding, IVs, nonces, authentication, key hygiene — make the difference between “we use AES” as a checklist item and a system that’s actually robust.

About

Italy

A quick note about me.

Portrait of Mario Ciavarella

I’m Mario, a finance graduate who keeps hands-on with code, electronics and AI; I build small but complete things to grow, learn and show what I can do with humility.

What I’m exploring

Ledger visualisations, governance tooling, small creative coding detours.

Current stack

TypeScript, Astro, SQL and Tailwind CSS, with containerized infrastructure on Docker.

How I keep myself honest

  • I define constraints early; it keeps the work grounded and prevents scope drift.
  • I surface unclear parts as soon as I spot them. Ambiguity gets expensive fast.
  • I test with my future self in mind — I'm often the one maintaining the code later.
  • I share progress in small steps; shorter feedback loops make everything smoother.

Contact

Open for new projects and collaborations.

Happy to trade notes or debug a half-finished idea.

I'll be in touch soon.