Using the OWASP Top 10 for LLM Applications in a Real Security Program
Use the OWASP LLM Top 10 as a risk index, then map each relevant item to a deployed path, control, and test.
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Security thinking for the agentic era.
Practical guidance, independent reviews, and clear explanations for teams building AI agents that can take real action.
AI Governance Best Practices That Hold Up in Production
Effective AI governance assigns owners and decisions to real systems, then checks whether controls still work after change.
Read articleAI Privacy: Trace the Data Before You Trust the Answer
AI privacy work starts with a traceable data flow: what enters, where it persists, who can retrieve it, and what leaves.
Read articleHow to Audit an AI System Without Turning It into a Paper Exercise
Audit an AI system by tracing its decisions, data, tools, and real effects rather than reviewing policy documents alone.
Read articleAI Risk Management That Reaches the Release Gate
A risk register becomes useful when every important risk maps to an owner, control, test, release decision, and recovery action.
Read articleChatGPT Business vs Enterprise: The Security Questions That Decide the Upgrade
ChatGPT Team is now ChatGPT Business. The upgrade decision depends on required controls and contract terms, not a larger model menu.
Read articleChatGPT Enterprise vs Claude Enterprise: Compare the Work Boundary, Not the Demo
Both products offer enterprise controls. The deciding evidence comes from the exact workspace, connectors, data paths, and agentic workflows your team enables.
Read articleAI Governance vs AI Agent Governance: Policy Is Not Runtime Control
AI governance sets organization-wide rules. Agent governance turns those rules into controls for identities, tools, actions, and runtime evidence.
Read articleQwen vs Llama: Choose the Model, Then Secure the Agent Around It
Qwen and Llama are model families, not fixed products. A fair comparison starts with exact variants and ends with a matched agent harness test.
Read articleHuman-in-the-Loop or Human-on-the-Loop? Put the Pause Where Failure Costs More
The choice is about when a human can stop an action and what evidence they have, not whether a dashboard includes an approval button.
Read articleLiteLLM MCP Security Review: Gateway Control Comes With a Wider Blast Radius
LiteLLM can centralize MCP access through an AI gateway. The same central position concentrates credentials, routing, and policy risk.
Read articleAuth0 MCP Server Review: Secure the Admin Path, Not Just the Login
Auth0's MCP server makes tenant administration accessible to AI clients. The decisive controls sit after login: scope, tool arguments, approval, and recovery.
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