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Data, permissions, compliance and supervision for deploying intelligent systems under control.
4 articles
Security & governance · AI Security
10 minThe right answer is not determined by the model location alone. Map data, logs, keys and access paths, then choose the level of control your risk and operating capacity actually require.
Read the analysisSecurity & governance · AI Security
8 minAn agent can treat an email, page or tool result as an instruction. Serious defense is not a protective prompt alone: separate trust levels, limit tools, log decisions and verify risky actions.
Read the analysisSecurity & governance · AI Security
12 minMCP makes it easier to connect AI agents to tools and data, but it does not secure those connections automatically. Here is the architecture, controls and evidence an enterprise should require.
Read the analysisSecurity & governance · AI Security
7 minThe OWASP Top 10 for 2025 shows that LLM application security extends beyond the model. Injection, sensitive data, supply chain, tools and cost must be controlled across the architecture.
Read the analysisLet us examine the process, data and decisions involved before choosing the technology.