Lock down your AI development environment

AI Development Security Audit

A structured review of how coding agents, MCP servers, and automation credentials are configured across your team, with a ranked remediation plan.

What this is

Coding agents shipped faster than most security policies did. Engineers now run tools that read the whole repository, execute shell commands, install packages, and connect to MCP servers nobody reviewed. Credentials end up in configuration files, agents get broad tokens because scoping was fiddly, and prompt injection through a fetched web page becomes a live code execution path. We audit the actual configuration on the actual machines and rank what to fix.

What is included

  • Agent permission and tool allowlist review across every developer machine
  • MCP server inventory with supply chain and trust assessment
  • Credential exposure scan across configuration, history, and environment
  • Prompt injection surface mapping for agents that fetch external content
  • CI and pipeline review where agents have commit or deploy rights

How we run it

  1. Inventory

    Which agents, which tools, which MCP servers, on whose machines, with what credentials.

  2. Assess

    Each finding scored on exploitability and blast radius rather than a generic severity label.

  3. Demonstrate

    For the top findings we show the actual path, because abstract risk never gets prioritized.

  4. Remediate

    Hardened baseline configuration plus a written policy your team can enforce.

  5. Re test

    Optional verification pass confirming the fixes hold.

What you receive

  • Findings report ranked by exploitability and blast radius
  • Hardened baseline configuration your team can roll out
  • Policy template covering agent use, tool approval, and credential handling
  • Remediation walkthrough session with your engineering leads
  • Optional re test after fixes land
Engagement
  • Typical duration1 to 2 weeks
  • Indicative investmentFrom $3,900
  • CategoryBuild
  • Starts withFree written quote
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Typical stack
Claude CodeMCPGAGitHub ActionsSSemgrepVVaultDDocker

Third party names and logos are shown for identification only and do not imply affiliation or endorsement.

Month one is refundable. If the first month does not land we return it. We would rather refund than carry a project neither side believes in.

The return

What this gives back, every month

Ranges, not promises. They come from published 2026 automation benchmarks and our own delivery data, and the audit re-runs them against your actual volumes before you commit anything.

1 to 2weeksfrom kickoff to a ranked, demonstrated remediation list
10 daysTo a ranked, demonstrated fix list
The first finding you would not have foundTime to break even
$3,900Your first year cost, all in

Why buy it

The case for doing this now

Coding agents outpaced your security policy

Engineers now run tools that read the whole repository, execute shell commands, install packages, and connect to MCP servers nobody reviewed. Most policies were written before any of that existed.

Broad tokens are the most common finding

Scoping credentials properly is fiddly, so it gets skipped. We find over-permissioned agent credentials in almost every environment we look at.

Prompt injection is a code execution path

An agent that fetches a web page and can also run commands has a route from untrusted content to your shell. That is worth an afternoon of somebody's attention.

Compared to the alternatives

What the same outcome costs elsewhere

Every option below solves some version of this problem. Here is what each one actually costs over twelve months.

First year cost of getting AI tooling configuration reviewed and hardened
In-house hire
$185,000
Assessment firm
$28,000
Typical agency
$9,000
deepaibots
$3,900

Figures are indicative market ranges for a team of 10 to 60 staff, not quotes from named vendors. Staff time is costed at $38 an hour loaded, meaning salary plus employment cost plus overhead.

Your optionsUpfrontOngoingTime to valueWhat you get
Do nothingNoneUnquantifiedNeverThe findings exist whether or not you look
In-house security engineerRecruiter fee$15,400/mo4 to 6 monthsFully loaded, and rarely AI tooling specialized
Assessment firm$20,000 to $40,000None6 to 10 weeksBroad scope, seldom covers agent configuration
deepaibots$3,900Optional re-test1 to 2 weeksSpecific to AI tooling, policy template included

What changed

Why this is worth buying in 2026 and was not in 2024

The scope of this service moved with the tooling. These are the shifts that make the engagement materially better than the same brief eighteen months ago.

  • 01

    MCP server supply chain became a live concern. Developers install community servers with the same casualness as npm packages, and those servers hold credentials.

  • 02

    Agent to CI integration spread quickly, which means an agent with commit rights is now a deployment path in many teams.

  • 03

    Published guidance for LLM and agent security matured enough that there is a defensible standard to audit against rather than improvised judgement.

FAQ

AI Development Security Audit: your questions

Is this a penetration test?

No. It is a configuration and process audit specific to AI tooling. It complements a penetration test rather than replacing one.

Do you need access to our code?

Preferably not. Most findings come from configuration, tool manifests, and permission scopes. We work read only wherever possible.

How disruptive is it to the team?

Roughly two hours per engineer across the engagement, mostly a walkthrough of their setup.

Get a fixed price for ai development security audit

The quote gives you a written scope and a fixed price. No obligation to proceed.