AI Data Provenance and Lineage: Building a Traceable Evidence Trail
Learn how AI data provenance and lineage track source, ownership, changes, retrieval, outputs, and actions across a business AI workflow.
Cybersecurity news, threat insights, and practical guidance for Canadian small and mid-sized businesses.
Find guidance for your situationChoose the outcome closest to the problem you are trying to solve.
Understand the difference between owning security tools and having active investigation and response.
Review the controls that protect inboxes, identities, sensitive messages, and payment workflows.
Learn how endpoint detection and response identifies behaviour that traditional antivirus can miss.
Build a layered ransomware strategy around business continuity rather than one defensive product.
Create a practical vulnerability-management process that focuses remediation on business risk.
Use the eight-pillar framework to govern AI inputs, retrieval, agents, outputs, and monitoring.
Learn how AI data provenance and lineage track source, ownership, changes, retrieval, outputs, and actions across a business AI workflow.
Learn what AI explainability means in practice, including purpose, data, limitations, controls, review, and evidence for business decisions.
Learn how hashes, signatures, provenance records, access controls, and runtime checks help verify that the approved AI model is running.
Learn how to test AI robustness across normal use, edge cases, malicious inputs, system changes, tool actions, and production monitoring.
Learn how to monitor concept drift, distinguish it from data drift, set thresholds, validate alerts, and respond when model performance changes.
Learn how Constitutional AI uses written principles and AI feedback to shape model behaviour, plus what businesses still need to control.
Learn how least privilege limits what AI agents can read and do, with a practical access review for Microsoft 365 and connected business tools.
A practical guide to validating prompts, files, retrieved content, tool output, and memory before an AI workflow uses them.
Learn how to protect OpenAI API keys with project separation, secure storage, permissions, monitoring, rotation, and incident response.
Learn how prompt jailbreaking bypasses AI safeguards, how it differs from prompt injection, and which controls reduce business risk.
Learn how to secure AI system prompts without treating them as secrets or access controls. Covers leakage, authorization, testing, and change management.
Learn the main vector database security risks and the controls that protect sensitive documents, embeddings, metadata, and RAG retrieval.
Turn AI governance decisions into technical controls, test evidence, monitoring, change approval, and a clear retirement process.
Use source checks, review levels, and accountable approval to keep plausible but unsupported AI answers out of business decisions.
Test whether business AI workflows expose data, exceed permissions, follow malicious instructions, or fail unsafely before production.
A practical guide to mapping the vendors, data flows, retention, access, and contracts behind an AI workflow.
A practical framework for governing ChatGPT accounts, data, connected systems, monitoring, and incident response at work.
Use a six-part review to check facts, sources, sensitive data, policy, tone, and actions before AI-generated work leaves the business.
Use MITRE ATLAS to turn realistic AI attack paths into practical testing, monitoring, and response controls.
Control the documents an AI can retrieve, who can retrieve them, and how retrieved content can affect an answer or action.
Give every AI agent a narrow job, its own identity, limited permissions, approval gates, and a clear shutdown path.
Make business AI behaviour reviewable with defined authority, enforceable rules, testing, monitoring, and accountable owners.
Understand how untrusted content can influence business AI systems, and the controls that limit the impact.
A practical control model for keeping sensitive business and client information out of unsafe AI workflows.