Most conversations about LLM security start at the wrong layer. They start with prompts — how to write better system prompts, how to filter inputs, how to add guardrails. But the vulnerabilities that matter most are architectural.
Read InsightCompanies are deploying LLMs into customer-facing systems, internal workflows, and autonomous agents. Most of them haven't accounted for the fact that these models can be manipulated through the very input they're designed to accept.
Read InsightOrganizations are treating AI security as something entirely new — a problem that requires new teams, new frameworks, and new thinking from scratch. It doesn't. The principles are the same. The attack surface is different.
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