Use Case

Prove What Your Coding Agents Saw

AI coding agents see your source code. When security or legal asks what left the building — which snippet, which model, when — you need a forensic answer, not a guess. AI Identity gives every interaction a cryptographically-signed audit trail that verifies offline.

The Challenge

Your code is your most valuable IP. AI coding assistants create new attack vectors.

Code Exfiltration

Coding assistants send your proprietary source to LLM providers. No visibility into what code leaves your environment or where it goes.

Shared Credentials

One API key for all coding agents across all repos. A leak in one repository compromises your entire fleet of AI assistants.

No Visibility

Which model saw which file? When? What was the response? Security teams are flying blind when AI assistants access source code.

How AI Identity Solves This

Complete visibility and control over every AI-code interaction.

Forensic Trail of Every Code Snippet

Every code interaction is HMAC-chained and DSSE-signed. When an IP-leak claim hits inbox, scrub through the exact sequence — which snippet, which model, which agent, what came back — and hand security a signed evidence bundle.

Per-Repository Identities

Each coding agent gets its own identity scoped to a specific repo or team. Audit trail attributes every action back to a specific repo + agent — no shared service-account guesswork.

Model Access Policies

Restrict sensitive repos to approved models only — block experimental or preview models. Every block writes to the audit chain so security can prove the controls were active.

Anomaly Detection

Bulk submissions, off-hours access, unauthorized model switching — flagged in real time. Anomalies become first-class events in the forensic chain, not after-the-fact log analysis.

See It in Action

Python

from ai_identity import AIIdentityClient

async with AIIdentityClient(api_key="aid_sk_...") as client:
    # Register a coding assistant for the payments repo
    agent = await client.agents.create(
        name="copilot-payments-repo",
        description="Coding assistant — payments service only",
    )

    # Restrict to approved models and working hours
    await client.policies.create(
        agent_id=agent.agent.id,
        rules={
            "allowed_models": ["gpt-4o", "claude-sonnet-4-20250514"],
            "blocked_models": ["*-preview", "*-experimental"],
            "time_window": {
                "start": "08:00",
                "end": "20:00",
                "timezone": "US/Eastern",
            },
        },
    )

    # Full audit trail of every code interaction
    logs = await client.audit.list(agent_id=agent.agent.id)
    print(f"Tracked {logs.total} code interactions")

Ready to put forensics on your coding agents?

We're onboarding design partners running production coding assistants. Get hands-on access, shape the v1.0 spec, lock in preferred pricing.

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