Governance for AI coding assistants like Claude Code, Cursor, GitHub Copilot, Codex, and Replit

DAXA prevents attacks before they happen. One control point governs what your source code, secrets, and IP can send to external models, what actions autonomous agents can take, and what every team spends on AI tokens.

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DAXA

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// See it in action — Claude Code & Codex

Watch DAXA govern AI coding assistants in real time

A live terminal session: a prompt carrying credentials, a policy hit in path, and a redacted completion the developer never has to think about.

LIVE DEMO

Real-time policy enforcement

See how DAXA inspects every request , applies context-aware policies, and delivers safe, compliant responses without slowing developers down.

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//COVERED ASSISTANTS

Every connected assistant in your stack

// How DAXA works

How DAXA governs every AI coding assistant

Coding assistants risk data in two places: at the inference layer, where prompts and completions travel to external models, and at the MCP layer, where agents connect to your data, tools, and systems. DAXA governs both from one policy engine, in path, with no workflow changes for developers. Four controls. Live in minutes.

DAXA Control Point: Safe Infer, Safe Agent, Policy + Audit Data

Inspect what leaves the IDE

Every prompt and completion is scanned in path. Secrets, credentials, and proprietary code are blocked or redacted before they reach an external model. via Safe Infer, at the inference layer

via Safe Infer, at the inference layer

Scope what agents can do

Every MCP call and tool call is validated against your policies. Agents stay bound to role and project. Unsafe actions never reach your systems, even the hijacked ones trying to exfiltrate context they were never meant to hold.

via Safe Agent, at the MCP layer

Set policy once, prove it everywhere

One policy plane across assistants, repositories, and regions. Full audit trail and real-time alerts to Slack and Splunk. Start in monitor mode. Enforce when you have the data. via Policy Plane

via Policy Plane

Prove every decision, on demand

Every prompt, retrieval, tool call, and cost event is captured with a tamper-evident audit trail, exportable per application. When an auditor, a regulator, or your board asks for evidence, it becomes a query rather than a project.
via Audit and Evidence

via Audit and Evidence

By 2028, Al coding costs will overtake the average developer's salary.

Dual-layer security for model and retrieval, EchoLeak-class defences, and developer-friendly integration in minutes.

// Built for your team

One platform. Two buyers. Zero friction.

Security leaders get control without slowing shipping. Engineering leaders get faster releases without cost surprises. Both work off the same policy plane, the same audit trail, and the same real-time enforcement.

// For Security Leaders

Security teams get control without slowing shipping.

Stop leaks at the source

Secrets, source code, and IP are blocked before they reach any external model. Classification runs on the assembled prompt in path, so sensitive context never becomes model context in the first place.

Govern every agent action

Access management extends into action management. Every retrieval, write, delete, and share is adjudicated against your policies in real time, no matter which agent, app, or model is behind the request.

Audit-ready by default

A tamper-evident record of every prompt, completion, and tool call, exportable per application. When an auditor asks for evidence, it becomes a query rather than a project. SOC 2 aligned and HIPAA-ready.

Live threat detection

Prompt injection, over-privileged agents, and out-of-scope writes are caught in path. Alerts fire to Slack and Splunk the moment a policy hits, not next quarter in a report.

// For Engineering Leaders

Engineering teams get faster shipping without cost surprises.

See AI spend by team and by coding agent

Track token usage and cost across Cursor, GitHub Copilot, Claude Code, and every other assistant your teams use. Drill down by team, by project, or by individual agent so you know exactly where the AI bill is coming from.

Set budgets and usage caps

Cap spend per team, per project, or per agent. Prevent runaway coding agents and unbounded loops before they land on the invoice. Governance owns the budget, not whoever shipped the feature.

Route smart, not expensive

Match each request to the right model based on complexity and sensitivity. Reserve frontier models for tasks that need them. Route everything else where it belongs, at a fraction of the cost.

Adoption without a rewrite

Drop in one JSON config per coding agent. Keep your IDE, your framework, and your model choice exactly as they are. Developers keep working the way they already work. Governance is invisible until it matters.

// Threats to AI-assisted coding

Know the threats facing your AI coding assistants

The AI coding assistants your teams already use introduce a category of risk that traditional endpoint, repository, and DLP tools cannot see. Filter by the assistant your team uses to explore the documented exploits, misconfigurations, and behaviors most relevant to your stack.

Showing 4 of 8 threats

Secrets in prompts

.env files, API keys, and credentials sent to external models before code reaches a repo.

Cursor

GitHub Copilot

Claude Code

Codex

Replit Agent

Auto-run destructive commands

Terminal agents execute shell commands with full developer permissions. Documented database deletions in the wild.

Cursor

GitHub Copilot

Claude Code

Codex

Replit Agent

Repository indexing exposure

Semantic indexes leak proprietary logic and cloud tokens outside DLP inspection.

Cursor

GitHub Copilot

Claude Code

Codex

Replit Agent

Injection via README

Malicious instructions hidden in repo artifacts hijack the assistant to exfiltrate .ssh keys.

Cursor

GitHub Copilot

Claude Code

Codex

Replit Agent

Showing 4 of 8 threats