Security & Privacy
Practical ways to protect business data, set safe boundaries, manage access, and test AI systems against misuse.
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pgvector for RAG: HNSW, IVFFlat, Filtering and Tenant Isolation
A practical guide to using pgvector in PostgreSQL for RAG, including index choice, metadata filters, recall, and tenant boundaries.
2 min read -
Prompt Injection in RAG: Why Retrieved Text Must Be Treated as Data
Prompt injection is not solved by a clever system prompt. Build safer RAG by separating instructions, evidence, permissions, and side effects.
2 min read -
MCP Authentication and Authorization Patterns for AI Agents
How to secure MCP servers with trusted identity, short-lived credentials, per-tool authorization, tenant isolation, delegated access, and misuse testing.
2 min read -
AI Agent Threat Modeling: Trust Boundaries, Tools and Recovery
Threat modelling for an agent can start with a simple story: what can it see, what can it change, and what happens if someone gives it misleading instructions?
2 min read -
Least Privilege for AI Agents: Tools, Data and Tenants
Least privilege lets an agent help with a real job without giving it a master key. Start with the person, the task, and the smallest useful capability.
2 min read -
Human Approval Patterns for AI Agents: Review the Right Boundaries
Human approval is most useful when a person is asked to judge one clear, consequential action with the evidence and context needed to take responsibility for it.
3 min read -
AI Agent Kill Switches and Rollbacks: Safe Recovery
A recovery plan should let you stop one unsafe workflow, understand what already happened, and resume safely instead of shutting down everything.
2 min read -
Retry, Timeout and Recovery Patterns for Agents
Retries are useful for temporary failures, but an indiscriminate retry can turn one uncertain request into three real-world side effects.
2 min read -
Avoiding Overpowered Tools in an Agent Integration
A tool that can do everything is easy to demo and hard to trust. Narrow tools make agent behaviour easier to understand, test, and stop.
2 min read -
What an AI Agent Should Never Be Allowed to Do
The core security and governance boundaries for tool-using AI agents, from secrets and private data to irreversible actions.
2 min read -
Human Approval Patterns for Autonomous Workflows
How to design useful approval checkpoints for AI workflows, including risk classification, review context, secure execution, expiry, and measurement.
2 min read -
AI Agent Incident Response: What to Do When an Agent Misbehaves
When an AI agent misbehaves, the first priority is to limit impact and preserve evidence. A calm incident process is more useful than trying to make the agent…
2 min read -
Permissions and Secrets for Production AI Agents
Practical controls for least-privilege agent tools, secret handling, delegated authority, prompt-injection resistance, and auditable production actions.
1 min read -
Secure Multi-Party Computation for AI: Benefits, Limits & RAG
Understand MPC threat models, practical privacy trade-offs and why secure retrieval alone does not make an AI assistant private or compliant.
6 min read -
Zero-Knowledge Proofs for AI: What Verifiable Inference Can Prove
What ZK proofs can establish for AI inference and RAG—and why a valid proof does not guarantee truth, privacy or compliance.
5 min read -
Blockchain for AI Audit Trails: Benefits, Limits & Alternatives
Learn what blockchain can add to AI audit logs—and what it cannot prove about accuracy, fairness or compliance. Compare privacy-aware designs and simpler alternatives.
7 min read -
Hybrid Cloud LLM Deployment: Data Flows, Latency & Trade-offs
A practical guide to hybrid LLM deployment: map prompts, logs and fallbacks; enforce placement policy; measure latency; and test privacy, cost and recovery assumptions.
5 min read -
Compliance RAG Systems: Traceability, Access & Human Review
Design compliance RAG with versioned sources, document-level access, checkable citations, privacy-aware audit evidence and human review—without treating an AI answer as legal advice or proof of compliance.
5 min read -
Federated Learning for RAG: Architecture and Privacy Limits
Federated learning can keep training data distributed, but model updates and shared outputs still need privacy controls. See how it differs from federated retrieval.
4 min read -
Cross-Border Data Transfer Compliance for Global RAG Deployments
Map prompts, embeddings, model calls, logs and support access in RAG systems; check official guidance and ask qualified counsel about transfer rules.
6 min read -
Authentication & Authorization for AI Chatbots: Safer Data Access
Secure chatbot access starts outside the prompt: distinguish sign-in from permission, authorize every retrieval and tool action, protect sessions, and test revocation, tenant boundaries and failure paths.
5 min read -
MCP Security: Authorization, Tool Safety & Data Boundaries
A practical MCP security guide to trusted servers, authorization, least-privilege tools, prompt injection, tenant isolation, logging and incident readiness.
8 min read -
Confidential Computing for AI: What TEEs Protect—and What They Don’t
A practical guide to trusted execution environments for AI: what TEEs and attestation can protect, what remains outside the boundary, and how to evaluate real-world trade-offs.
5 min read -
GDPR for AI Chatbots: A Practical Data Protection Checklist
A practical GDPR checklist for AI chatbots: clarify roles and lawful bases, map data flows, minimise retention, review providers and assess risk—without assuming consent or product compliance features.
6 min read