Encryption Consulting

The Model Context Protocol has become the default way enterprises connect AI agents to internal tools, databases, and APIs. That is exactly why it needs its own security model. An MCP server is not a read-only data source. It is an execution layer that can query a datab...

An AI agent does not pause to reconsider. Once it has a credential and a task, it keeps calling APIs, moving data, and triggering downstream actions at machine speed, with no built-in moment where it stops to ask whether it should. A person who makes a mistake usually catches it within one action. An agent with broad access and a long-lived credential can take dozens of c...

A shadow agent does not announce itself. It starts as a script someone scheduled to run every night, a copilot feature a SaaS vendor turned on by default, or a workflow wired up in an afternoon to save a team from copy-pasting between two tools. Six months later it is calling internal APIs, reading customer data, and nobody in security can say who owns it, what it is allo...

CyberArk recently framed the life and death of an AI agent as an identity security problem, comparing an agent’s existence to a human employee’s tenure: hired, trained, given responsibility, and eventually retired. DigiCert has built a similar case around what it calls an AI Agent Passport, and AppViewX has argued that agent identity is no longer a scale problem but a behavio...

An autonomous agent with too much access does not need a stolen password. It only needs a task, a set of tools, and nobody watching what it does with them.

Organizations that experienced an AI-related security incident in the past year were missing basic AI access controls 97% of the time, according to IBM’s 2025 Cost of a Data Breach Report, as cited in Entrust’s a...