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
Inventory
Which agents, which tools, which MCP servers, on whose machines, with what credentials.
Assess
Each finding scored on exploitability and blast radius rather than a generic severity label.
Demonstrate
For the top findings we show the actual path, because abstract risk never gets prioritized.
Remediate
Hardened baseline configuration plus a written policy your team can enforce.
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
- Typical duration1 to 2 weeks
- Indicative investmentFrom $3,900
- CategoryBuild
- Starts withFree written quote
Opens the quote form with AI Development Security Audit already selected.
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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.
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.
| Your options | Upfront | Ongoing | Time to value | What you get |
|---|---|---|---|---|
| Do nothing | None | Unquantified | Never | The findings exist whether or not you look |
| In-house security engineer | Recruiter fee | $15,400/mo | 4 to 6 months | Fully loaded, and rarely AI tooling specialized |
| Assessment firm | $20,000 to $40,000 | None | 6 to 10 weeks | Broad scope, seldom covers agent configuration |
| deepaibots | $3,900 | Optional re-test | 1 to 2 weeks | Specific 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.
Related
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Ship a real product, not a demo
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- Multi tenant from migration one
- Admin panel included
- You own the repository
Enterprise Agent Stack Setup
Our internal agent runtime, deployed in your environment
- Runs in your own cloud
- Secrets never touch prompts
- Full audit trail
- Security pack for procurement
AI Agent Development
Production agents that ship and ship again
- Runs 24/7
- Escalates when unsure
- Every decision logged
- No extra headcount
Get a fixed price for ai development security audit
The quote gives you a written scope and a fixed price. No obligation to proceed.