LEDGERsigned · hash-chained · verifiable offlinePOLICIESplain english · compiled · enforced inlineRED TEAMcontinuous adversarial probing on shadow twinsCOMPLIANCESOC 2 · GDPR · HIPAA · PCI-DSS · EU AI Act · ISO 42001INTEGRATIONgateway · SDK · sidecar · no rewritesLEDGERsigned · hash-chained · verifiable offlinePOLICIESplain english · compiled · enforced inlineRED TEAMcontinuous adversarial probing on shadow twinsCOMPLIANCESOC 2 · GDPR · HIPAA · PCI-DSS · EU AI Act · ISO 42001INTEGRATIONgateway · SDK · sidecar · no rewrites
Teleon / Blog

Agentic security, in plain terms.

Practical guidance on securing AI agents, tools, and the systems they act on, written by the team building the trust layer for AI agents.

AI Security

A First 30-Day AI Security Plan

The first 30 days of an AI security effort should produce an inventory, a risk ranking, fixes to the worst gaps, and a lightweight review process, not a full program.

AI SecuritySeptember 23, 2026
AI Security

AI Security Questions Every CISO Should Ask

A CISO's AI security questions should focus on inventory completeness, enforcement consistency, evidence quality, and whether existing programs actually cover agents.

AI SecuritySeptember 23, 2026
AI Security

AI Security Questions Every CTO Should Ask

A CTO does not need to review AI security code directly, but should be able to get a specific answer to a short set of pointed questions from any team building it.

AI SecuritySeptember 23, 2026
AI Security

How to Review an AI Feature Before Production

A pre-production AI review should check data access, tool authority, failure behavior, and monitoring readiness, with specific questions rather than a general sign-off.

AI SecuritySeptember 23, 2026
AI Security

Common AI Security Architecture Mistakes

Most AI security architecture mistakes come from trusting the model as a boundary, sharing credentials across tools, and skipping authorization on retrieval.

AI SecuritySeptember 23, 2026
AI Security

How to Define Acceptable AI Behavior

Defining acceptable AI behavior means writing rules specific enough to enforce in code, not general values that a model interprets differently every time.

AI SecuritySeptember 23, 2026
AI Security

What Security Teams Should Log in AI Applications

Security teams should log identity, policy decisions, tool calls, and outcomes for AI activity, not raw prompts by default, to avoid turning logs into a liability.

AI SecuritySeptember 23, 2026
AI Security

Why AI Activity Needs an Audit Trail

An audit trail turns "we think this is what the agent did" into a verifiable record, which is what actually matters during an investigation or a compliance review.

AI SecuritySeptember 23, 2026
AI Security

The Role of Policy Enforcement in AI Security

Policy enforcement turns written AI security rules into decisions applied consistently at runtime, closing the gap between a document and what an agent actually does.

AI SecuritySeptember 23, 2026
AI Security

AI Security for Enterprises: A Practical Operating Model

Enterprise AI security works best as a federated model, a small central team setting standards and tooling while product teams own their own agents' risk.

AI SecuritySeptember 23, 2026
AI Security

AI Security for Startups: What to Protect First

A startup shipping AI features should protect tool authorization, data access, and customer data first, before investing in monitoring maturity it cannot yet staff.

AI SecuritySeptember 23, 2026
AI Security

How to Build an AI Security Program

An AI security program needs an inventory, clear ownership, layered controls, and a monitoring loop, built incrementally rather than launched all at once.

AI SecuritySeptember 23, 2026