Qcrypton - Quantum and Crypto as a Service

The convergence of large language model deployments and fault-tolerant quantum computing creates a dual threat landscape that no existing tool addresses holistically. **QCrypton: Quantum-Safe Security for the AI Era** presents the architecture, implementation, and real-world deployment of a unified security platform that bridges these two domains. Based on seven peer-reviewed research publications, this book covers an 11-scanner AI threat detection engine capable of identifying prompt injection, MCP tool poisoning, and novel "rug-pull" attacks; a parameterized fault-tolerant quantum computer attack cost estimation engine modeling 28 cryptographic algorithms; a zero-native-dependency post-quantum cryptographic toolkit implementing HPKE, LSH-256, and BB84 quantum key distribution; the first code scanner to encrypt its own findings using QKD-derived keys; and a stateless cloud-native architecture achieving 99.97% availability with horizontal scaling. Essential reading for security engineers, CISOs, and researchers preparing for the post-quantum era. The world stands at the intersection of two transformative shifts reshaping cybersecurity. Large language models introduce new attack classes — prompt injection, tool poisoning, data exfiltration — that traditional tools cannot detect. Simultaneously, quantum computing advances toward breaking RSA, elliptic curve cryptography, and reducing AES security margins. These threats are deeply intertwined: AI systems handle data protected by quantum-vulnerable algorithms, and adversaries conducting harvest-now-decrypt-later attacks are collecting encrypted data today. Yet security tools treat these as separate problems. AI frameworks ignore cryptographic posture. Quantum scanners ignore AI attack surfaces. This fragmentation creates blind spots at the intersection. This book presents QCrypton, the first unified platform addressing both AI threats and quantum vulnerabilities as complementary concerns. It is production-grade software — over ten thousand lines of code, deployed on Kubernetes with horizontal scaling, multi-tenant isolation, and enterprise authentication. Based on seven research publications, it takes readers from threat landscape to production deployment. QCrypton's five-layer architecture provides bidirectional integration: threat scanners invoke quantum vulnerability assessments in real time, while detected secrets are encrypted via BB84 quantum key distribution before reporting. The eleven-scanner threat engine detects prompt injection (22+ rules), MCP tool poisoning (8 checks including novel rug-pull detection), data exfiltration (10 vectors), and quantum cryptographic vulnerabilities across 28 algorithms. The FTQC estimation engine computes physical qubit requirements using surface code error correction with magic state distillation, providing concrete timelines: "RSA-2048 is vulnerable by ~2035 with ~20M physical qubits." The zero-dependency post-quantum toolkit implements HPKE (RFC 9180), LSH-256 (KS X 3262), and BB84 QKD using only Node.js built-in primitives — eliminating supply-chain risk entirely. The cryptographic code scanner covers six languages, generates CycloneDX CBOMs, and provides CI/CD quality gates. QKD-protected secret reporting solves the paradox where scanners expose detected secrets in plaintext reports. BB84-derived AES-256-GCM encryption wraps every finding before it leaves the process. The stateless cloud-native architecture achieves 96% scaling efficiency at 10 replicas, sub-4ms authentication, and 99.97% availability over 30 days. Each chapter connects research to practice: implementation details, real-world use cases across financial services, healthcare, and defense, and open challenges for future research. **Who This Book Is For** Security engineers, software architects, CISOs, Compliance Officers, and researchers working at the intersection of AI security and post-quantum cryptography.