Building a Visual Guide to PQC Handshakes

We are living on the cusp of a cryptographic revolution. For decades, the bedrock of internet security — everything from the HTTPS padlock in your browser to your secure messaging apps — has relied on public-key cryptography like RSA and Elliptic Curve Diffie-Hellman (ECDH). These systems work because they are based on math problems that classical computers find incredibly difficult to solve, like factoring massive numbers. But there is a ticking clock. Quantum computers are evolving rapidly. When a cryptographically relevant quantum computer (CRQC) arrives, it will run an instruction known as Shor’s Algorithm . To a quantum computer running Shor’s Algorithm, RSA and Elliptic Curves aren’t complex puzzles — they are wet tissue paper. They will be broken instantly. Worse yet, bad actors are practicing “Harvest Now, Decrypt Later” (HNDL). They are intercepting and storing encrypted traffic today, waiting for the day a quantum computer can unlock it. To combat this, the National Institute of Standards and Technology (NIST) finalized its official Post-Quantum Cryptography (PQC) standards, including FIPS 203 (ML-KEM) . To explore this shifting landscape, I decided to build a full-stack web application: the PQC Handshake Visualizer . My goal was simple: demystify the new post-quantum handshake and prove just how easy it is for everyday developers to implement quantum-resistant security right now. The Project: Inside the PQC Handshake Visualizer The application is a slick, dashboard-driven visualizer. It simulates a live Key Encapsulation Mechanism (KEM) handshake between a Server (Alice) and a Client (Bob). Instead of traditional key exchange, where two parties negotiate a key across a wire, post-quantum protocols use a KEM cycle. The visualizer maps this entire interaction out using three distinct phases: Key Generation (Phase 1): The server generates an ML-KEM-768 public/private keypair. Encapsulation (Phase 2): The client takes the server’s public key and wraps (“encapsulates”) a randomly generated symmetric shared secret inside a heavy ciphertext payload. Decapsulation (Phase 3): The server receives the ciphertext, opens it using its private key, and extracts the exact same shared secret. The UI animates these packets flying back and forth, printing out live console metrics showing execution speeds and exact payload sizes. The Secret under the Hood: Quantum-Proofing is Now a One-Liner When I started planning the backend, I expected to get bogged down in complex C++ bindings or massive native binaries to handle the high-dimensional polynomial vectors that lattice-based cryptography requires. Instead, I discovered that the open-source community has already done the heavy lifting. I used an incredibly elegant, audited, pure JavaScript/TypeScript library called @noble/post-quantum developed by Paul Miller. Because of modern tooling, quantum-proofing the entire backend logic inside my server.js file took only a few intuitive lines of code. Here is the exact code executing the core cryptographic endpoints: JavaScript import { ml_kem768 } from '@noble/post-quantum/ml-kem.js'; // Phase 1: Server generates a quantum-resistant keypair const keyPair = ml_kem768.keygen(); const publicKey = keyPair.publicKey; const privateKey = keyPair.secretKey; // Phase 2: Client encapsulates a secret using the Server's public key const { cipherText, sharedSecret } = ml_kem768.encapsulate(publicKey); // Phase 3: Server decapsulates the ciphertext using its private key const serverSharedSecret = ml_kem768.decapsulate(cipherText, privateKey); That’s it. No complicated math formulas, no multi-threaded setups. The exact same architecture we’ve used for years with standard crypto libraries fits perfectly into the post-quantum paradigm. If you can handle a basic npm package, you can secure data against a quantum computer. The Catch: Understanding the Cryptographic Overhead While implementing the code is remarkably straightforward, the visualizer highlights a massive physical reality of post-quantum cryptography: The Payload Tax. Legacy elliptic curve algorithms like X25519 are incredibly lightweight. An X25519 public key is a tiny 32 bytes. Its ciphertext payload is also just 32 bytes. It fits cleanly into a single network packet without anyone noticing. ML-KEM, because it relies on massive lattice vector structures to confuse quantum algorithms, requires drastically more data. My visualizer tracks these bytes in real-time to show the stark contrast: ML-KEM-768 Public Key: 1,184 Bytes (A 37x expansion over legacy ECC) ML-KEM-768 Ciphertext: 1,088 Bytes (A 34x expansion over legacy ECC) When you trigger the handshake in the UI, you are reminded that while the math is incredibly fast (executing in fractions of a millisecond on standard hardware), our network architecture will feel the weight. Moving kilobytes of key material instead of bytes means network engineering teams must prepare for packet fragmentation and minor latency increases during initial handshakes. Final Thoughts: Build For Tomorrow, Today Building the PQC Handshake Visualizer taught me that the transition to the quantum age isn’t a distant problem for academic researchers — it is a tangible development task happening right now. We don’t need to reinvent the wheel or wait for breakthrough commercial tools. The libraries are open-source, the standards are finalized by NIST, and the implementation requires nothing more than a standard Express server and a couple of API endpoints. If you are a developer building an application, look into hybrid handshakes or post-quantum modules today. The code is ready. The tools are here. It’s time to start quantum-proofing your portfolio. Here is my code: https://github.com/damianwgriggs/Post-Quantum-Cryptography-Showcase \