CyphrQCI/CD for LLM Applications: How to Ship AI Features Safely
How to ship LLM features safely: version prompts and model IDs, gate releases on evals and red-team tests, secure the model supply chain, and roll back.
AI Security
How AI systems get attacked, and the controls that hold: prompt injection, agents, permissions and audit.
9 articles
MCP Security Explained: Tool Poisoning, Token Risks and Controls
What the Model Context Protocol is, how MCP servers and tools get abused, real CVEs, and the fixes: allowlists, pinned versions, narrow scopes, approval.
OpenAI Security Explained: Model Safeguards, Data Rules and Gaps
How OpenAI secures frontier models and business data: Preparedness Framework, SOC 2 and ISO scope, retention, ZDR, and what isn't verified.
AI Agent Security Architecture: Seven Layers and Their Controls
A layer-by-layer map of an AI agent's attack surface, from prompt to credentials, with the controls, OWASP and ATLAS IDs and logs each layer needs.
AI Coding Assistant Security: Data, Admin Controls and Code Review
What Claude Code, Continue, Cursor and GitHub Copilot send out, the admin controls that limit them, and the repo rules that still need a human.
Anthropic Security: How It Protects Its Models and Customer Data
Anthropic security from its own pages: ASL-3 weight protection, ISO and SOC 2 claims, data retention, zero data retention, and what's unverified.
AI Agent Security Risks at Work: The Guardrails That Matter
What an AI agent is, why letting AI act brings new security risks, and the guardrails, vendor questions and 10-point checklist a manager needs.
Prompt Injection Explained: What It Is and How to Protect Your Team
Prompt injection in plain language: how hidden instructions trick AI tools, why AI agents raise the stakes, and five defences any manager can use.
Shadow AI at Work: How to Find the AI Tools Your Team Already Uses
Shadow AI at work is AI your team uses without approval. How to find it in consent, network and expense records, and what to offer instead.