Safety
8 articles
SecurityQuantum-resistant and AI-era security: what is done and what is not
What is post-quantum on Tenzro Network today, what stays classical and why, how machine identity, agents with owners, signed releases and adversarial testing fit together, and an explicit list of what is not done.
5 min read
Payments for machinesSpending limits and revocation for agents
When software spends money, someone has to answer for it. That takes a responsible party behind every agent, limits the agent cannot raise itself, and a revocation that stops payment on every rail at once. How each of those works on Tenzro, and why each has to be enforced outside the agent.
5 min read
Enterprise AIAgentic AI in the Enterprise: Delegation You Can Audit
When agents call tools and spend money, governance has to move from policy documents into the systems that authorize each action. A delegation model, a control checklist and the records an auditor will ask for.
5 min read
SecuritySecuring the AI Model Supply Chain, From Weights to Serving
A model file is executable risk: it can carry code, be swapped in transit or be served by a machine that is not what it claims. A layered control set for model provenance, safe formats, signed releases and attested serving.
5 min read
SafetyDesigning Safe Harnesses: Scopes, Limits, Expiry and Revocation
Prompt injection will sometimes succeed, so an agent's safety has to live outside the model. How Tenzro bounds every delegated agent with consensus-enforced scopes, spending limits, expiry, step-up approval and revocation, with an accountable root behind each one.
5 min read
Sovereign AIEU AI Act, NIS2 and the Data Act: a guide for AI operators
Three EU laws now shape how AI infrastructure is run in Europe. This guide sets out the dates that apply after the 2026 Digital Omnibus on AI, the obligations that reach operators, and the evidence worth producing by default.
7 min read
Open modelsOpen models need open infrastructure: provenance and licenses
Once open weights are released, the builder loses sight of how they are served. This article covers what model builders should expect from the infrastructure that serves their work: proof of which weights ran, license terms enforced in the serving path, gated access that holds, and attribution that reaches the user.
5 min read
Public sectorPublic Sector AI: Buying Capability Without Buying Lock-In
Governments in the US, UK and EU now tell agencies to avoid AI vendor lock-in, protect government data from commercial training and assess impacts before deployment. A procurement checklist that turns those policies into contract terms and architecture.
4 min read