AI agents are useful, but their access paths are not yet governed.
Kavryl identified multiple AI agents, MCP servers, and LLM-connected automation paths with access to sensitive SaaS and cloud systems. The highest-risk issue is a support automation agent that can read customer records, access Google Drive documents, and post outbound Slack messages without consistent human approval.
The dangerous path is the combination of sensitive read access and outbound communication. A malicious ticket, document, or Slack message could instruct the agent to summarize or forward sensitive customer data into the wrong destination.
First 7 days
Disable unnecessary shell tools, add approval for outbound messages, remove unused connectors, and assign owners to every agent.
First 30 days
Move agents to least-privilege OAuth scopes, create separate service identities, and add retrieval-time authorization.
First 90 days
Build recurring agent permission review, MCP approval policy, continuous scanning, and audit-ready AI security posture documentation.
Findings are mapped to OWASP LLM risks, OWASP Agentic AI guidance, and MITRE ATLAS concepts where relevant. Kavryl uses these frameworks to make agent risk easier to explain to executives, auditors, and engineering teams.