Whitepaper

The Zero-Trust Communication Layer Your Infrastructure Needs

Most modern applications rely on HTTPS/TLS, but in real-world deployments TLS is often terminated by intermediaries such as CDNs, WAFs, load balancers, API gateways, and service meshes. Once TLS terminates, sensitive data may be visible to infrastructure components, logs, and operators that are not the application itself.

This problem is amplified in AI systems, where prompts, retrieved documents, embeddings, and responses often contain proprietary or regulated data. OwnWire reduces this exposure by encrypting message payloads at the application layer so that intermediaries see ciphertext only. Decryption happens only inside the OwnWire runtime and is forwarded privately to an internal client.

Problem Statement

TLS protects data in transit between two endpoints, but in modern architectures the "endpoint" is often infrastructure rather than the application. This creates a large trust surface. AI pipelines multiply this problem because data flows through many services, each a potential leakage point.

What OwnWire Does

OwnWire adds application-layer payload encryption on top of WebSockets. Messages are encrypted before traversing infrastructure and decrypted only at a controlled private boundary. OwnWire exposes a public WebSocket for browsers/SDKs and a private internal WebSocket for backend or LLM clients.

Implementation Overview

OwnWire uses ephemeral ECDH on P-256 (or the more secure X25519) to establish a per-session shared secret. Keys are derived using HKDF-SHA256 and used with AES-256-GCM for message encryption. Each message includes a random salt and sequence number to ensure nonce uniqueness and prevent replay.

Decryption and Trust Boundary

Payloads are decrypted only inside the OwnWire runtime and forwarded as plaintext over a private internal interface, typically bound to localhost. Plaintext exists only where computation occurs and is not exposed to proxies, logs, or observability systems.

Security Properties

OwnWire prevents intermediaries such as CDNs, WAFs, load balancers, and logging layers from accessing payload contents. Infrastructure can route traffic but cannot read it.

Threat Scenarios Addressed

OwnWire specifically protects against the following real-world threat scenarios:

• CDN compromise or malicious CDN employee — Encrypted payloads remain unreadable even with full CDN access
• Cloud provider compliance audits — Logs contain only ciphertext, not sensitive plaintext data
• Third-party WAF vendors — WAF can inspect traffic patterns but cannot decrypt message contents
• Internal platform teams — Infrastructure engineers see encrypted traffic only
• Observability systems — Monitoring and logging tools cannot expose payload data

Use Cases

OwnWire is particularly valuable in scenarios where sensitive data flows through shared infrastructure:

• RAG (Retrieval-Augmented Generation) pipelines where documents contain PII or proprietary information
• Healthcare chatbots handling PHI (Protected Health Information) across CDN infrastructure
• Financial advisory systems processing proprietary trading signals or customer financial data
• Customer support AI with access to sensitive account information and support history
• Multi-tenant SaaS platforms where infrastructure is shared across customers
• Compliance-sensitive environments requiring data minimization and access controls

Limitations

OwnWire does not protect against a fully compromised host running OwnWire or the internal client. Metadata outside the encrypted payload may still be visible unless explicitly encrypted by the application.

Compliance Impact

By reducing the number of systems that can access sensitive payload data, OwnWire supports data minimization principles and simplifies SOC 2, GDPR, and CCPA narratives.

Conclusion

OwnWire addresses a practical gap in modern systems where TLS alone is insufficient. By encrypting payloads at the application layer and decrypting only at a controlled boundary, OwnWire reduces leakage surface and makes secure AI messaging practical.