Anthropic's New Compliance API for Claude Code: What It Shows, What It Misses

Key points

• Anthropic has released new Compliance API endpoints for Claude Code, giving security teams their first direct feed of agent activity on developer machines.
• Claude Code can read files, execute shell commands, and call outside tools using whatever credentials the developer already has.
• Activity logs show what an AI agent did, but not whether the access itself was legitimate under company policy.
• Governance frameworks such as the NIST AI Risk Management Framework and the EU AI Act push organisations to document and control automated decision systems, including coding agents.
• Security teams are being told to treat AI coding assistants as a new class of identity, not as a feature bolted onto an existing developer account.

Anthropic has quietly opened a door security teams have been asking about for months. Its new Compliance API endpoints for Claude Code, the company's AI coding assistant, let enterprises pull activity records showing what the agent did on a developer's machine. That includes files it read, shell commands it ran, and outside tools it called through the Model Context Protocol, a standard way for AI assistants to plug into other software.

That visibility matters. It is also not enough on its own.

What does the Compliance API actually show?

The endpoints give security and compliance teams a record of Claude Code's actions inside an organisation. Until now, most of that activity sat on individual laptops with no central log. The new feed changes that, at least for customers on Anthropic's enterprise plans.

Think of it as a flight recorder. It captures what happened. It does not tell you whether the flight should have taken off.

As The Hacker News noted in its coverage, Claude Code operates with the same credentials as the developer running it. If a developer has access to a production database, so does the agent sitting on their machine. The Compliance API will show you the query. It will not tell you whether the agent should have been trusted to run it.

Why is this a policy problem, not just a logging problem?

Because AI agents are starting to look like a new kind of user, and most identity governance rules were written before they existed. Regulators are catching up. The NIST AI Risk Management Framework, published in January 2023, asks organisations to map, measure and manage risks from AI systems that take actions on behalf of humans. The EU AI Act, which entered into force on 1 August 2024, imposes staged obligations on providers and deployers of AI systems, with general-purpose model rules applying from 2 August 2025 and high-risk system obligations phasing in through 2027.

Neither framework was written with coding agents specifically in mind. Both apply.

For security teams, the practical question is narrower: who or what is accountable when an AI agent, running under a developer's identity, deletes a table or leaks a secret? Today, in most companies, the honest answer is the developer. That answer will not hold for long.

What should security teams do now?

Start by treating the coding assistant as its own identity, even when it borrows a human one. That means pulling the Compliance API feed into the same monitoring pipeline as other privileged activity, and writing policies that say what an agent may and may not do without a human in the loop.

The harder work is upstream. If a developer account has standing access to production, the agent inherits that access the moment it launches. Just-in-time credentials, scoped tokens, and separate service identities for AI tooling all help. So does a plain-English written policy telling engineers when it is acceptable to point Claude Code at customer data.

Logs answer the question of what happened. Governance answers the question of what should have been allowed. Anthropic has given enterprises the first. The second is still on the customer.