Published March 4, 2026 | Version v3
Publication Open

Cryptographically Self-Verifying Systems: Backend-Blind Veriability in Adversarial Environments

Authors/Creators

  • 1. Independent Security Researcher

Description

High-stakes digital processes—such as coordinated vulnerability disclosure, zero-day handling, regulatory filings, and compliance attestations—require confidentiality until a defined disclosure event, together with integrity, authenticity, and non-repudiation. Most existing systems rely on trusted infrastructure, privileged operators, or internal logs, assumptions that are increasingly fragile in the presence of breaches and insider threats.

We introduce Cryptographically Self-Verifying Systems (CSVS), a system-level design pattern that makes operational infrastructure untrusted by design. CSVS enables any third party to verify correctness post hoc using only publicly observable artifacts, even when the infrastructure is fully malicious, while relying only on a semi-honest disclosure authority. A key property is Backend Blindness: the infrastructure cannot access or distinguish protected payloads prior to authorized disclosure, enforced purely by the semantic security of hybrid encryption with mandatory length-hiding padding.

We formalize CSVS under a fully adversarial infrastructure model and prove confidentiality, integrity, authenticity, non-repudiation, and Backend Blindness from standard cryptographic assumptions. We further provide low-overhead, verifiable relative temporal ordering via optimized hash chaining, combined with independent publication mechanisms to prevent suppression. We evaluate security, performance, and limitations, and demonstrate applicability through case studies in vulnerability disclosure, regulatory compliance, and research integrity.

This version substantially extends the initial preprint with a formal adversarial model, protocol specification, security proofs, and evaluation.

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Monti-2026-CSVS-Backend-Blindness.pdf

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Additional details

Related works

Is supplement to
Software: https://github.com/juanmonti/csvs (Other)