Insights · Security

Security
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Filtered field notes for Security work, newest first.

Security2026 · 09 · 15

Securing Packages, Container Images, and SBOMs

Build a traceable and verifiable software supply chain across dependencies, container images, and SBOM operations.

Security2026 · 09 · 11

Designing Fine-Grained Authorization for Enterprise APIs

Enterprise API authorization must control not only which endpoint may be called, but also which records, fields, and business states are accessible.

Security2026 · 09 · 07

Auditing Dormant and Overprivileged Service Accounts

A practical method for inventorying machine identities, validating real usage, and reducing access without disrupting production systems.

Security2026 · 08 · 10

API Keys, OAuth, and Service Accounts: Drawing the Right Identity Boundaries

A practical framework for choosing and governing API keys, OAuth tokens, and service accounts across enterprise integrations.

Security2026 · 08 · 10

Encryption and Key Management Checks Before Cloud Data Landing

A practical engineering checklist for choosing encryption boundaries, controlling keys, and validating recovery before cloud ingestion.

Security2026 · 08 · 09

Beyond Shared Folders: Document Classification and Access Logging for Enterprise Knowledge Bases

A practical engineering guide to classification, authorization inheritance, RAG controls, and useful audit trails for enterprise knowledge bases.

Security2026 · 08 · 09

Where to Place Prompt Injection Defenses

Prompt injection is not solved by one filter; this guide places controls across ingestion, RAG, tool execution, output, and operations.

Security2026 · 08 · 08

Threat Modeling Before Connecting AI Assistants to Internal Systems

A practical framework for defining trust boundaries, permissions, abuse paths, and failure controls before an AI assistant can access enterprise systems.

Security2026 · 07 · 04

Designing Audit Trails and Traceability for AI Output

AI systems need evidence chains that explain how an output was produced, what data shaped it, and who acted on it.

Security2026 · 07 · 03

The Security Baseline for Enterprise AI

Before scaling enterprise AI, define data boundaries, identity controls, model/vendor rules, and auditability as engineering requirements.

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