Topic starter
02/08/2026 11:35 am
TL;DR: Claude is moving from a prompt-based assistant into a tool-connected workspace that can access files, shells, Slack, GitHub, and databases, creating shadow AI, connector, and code-security risk across the enterprise according to Akto. The governance gap is no longer adoption, but identity oversight for non-human access, autonomous workflow boundaries, and data handling controls.
Editorial analysis by NHI Mgmt Group, based on content published by Akto: “Top 6 Claude Security Risks: As AI Becomes Your Employees' Operating System”.
Key questions
Q: What breaks when Claude usage is not centrally discovered and governed?
A: Security teams lose the ability to see which employees, projects, and connectors are moving data through Claude.
Q: Why do Claude connectors increase enterprise risk so quickly?
A: Because connectors turn Claude from a text interface into a delegated access path to Slack, GitHub, Google Drive, and other systems.
Q: How should teams govern AI agent skills in production?
A: Treat skills as controlled runtime assets, not informal text.
Practitioner guidance
- Map every Claude entry point Inventory claude.ai, desktop usage, Claude Projects, Code, Cowork, and connected systems so you can see where access already exists.
- Review connector permissions and authentication Check which Slack, GitHub, Google Drive, Jira, and Notion integrations are active, what OAuth scopes they hold, and whether any connector was enabled without security review.
- Treat Claude Projects as persistent data stores Classify uploaded documents, shared project spaces, and linked data sources as durable enterprise repositories, then apply data handling controls to them.
Bottom line: Claude has shifted from a productivity assistant to a governed access surface that can reach files, code, and production systems.
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02/08/2026 12:49 pm
Claude has become an IAM problem because its real risk is delegated access, not prompt quality. Akto's core point is that Claude now operates through files, shells, Slack, GitHub, and databases with the same privileges as the user. That makes identity the control surface, because the security question is who granted access, what it can touch, and whether anyone can still govern it. Practitioners should treat tool-connected AI as a privilege-bearing identity class.
A few things that frame the scale:
- 67% of organisations still rely heavily on static credentials despite the risks they pose to agentic AI deployments, according to the 2026 Infrastructure Identity Survey.
- Only 13% of organisations feel extremely prepared for the reality of agentic AI despite the majority racing toward autonomous adoption, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: How do identity teams account for autonomous collaboration in AI tools?
A: By extending governance to actions taken by the system, not only by the employee who enabled it. That means defining which tasks Claude may perform, what data it may access, and how those actions are audited. Without that layer, accountability sits with the human while the operational behaviour belongs to the machine.
👉 Read our full editorial: Claude security risks are now an IAM and NHI problem