AI Application Security Snapshot
Read-only review
A review of how the application is built, configured, and exposed, with no testing against a running application. You receive a plain-language brief of what stands out and what to address first.
AI wrote the code. Who checked the architecture?
Independent security and architecture review for software built with AI tools, and for the regulated firms that put client data inside it.
CISSP. 30 years securing sensitive data in regulated environments. 10+ years at Microsoft.
Working software is not the same as secure software.
AI coding tools are very good at producing an application that runs. Whether it holds up against real users, real client data, and someone actively trying to get in is a separate question.
In Veracode's 2026 GenAI Code Security Report, roughly 44% of tested code generation tasks produced code with a known security vulnerability when the prompt gave no security guidance.
Read it carefully. This is a security vendor's benchmark of model output on standardized tasks. It measures generated code, not deployed applications.
Often the larger risks are architectural: which platform hosts the application, where secrets and client data are stored, who has access, what each integration is allowed to do, and which defaults were accepted without a second look. Those decisions are made early, frequently by the tool itself, and they are expensive to change after launch.
Two situations bring people to this work.
Regulated firms vetting an AI-built application
A vendor tells you their product was built with AI tools. Or your firm is about to put client data into a new AI application. Before it goes live, you need to know where the data goes, who can reach it, and what the vendor can actually show you.
What you get
- A written assessment for your vendor due diligence file
- Questions to put to the vendor, and how to read the answers
- A clear view on whether the risk is acceptable
Founders and small teams building with AI
You built something real with AI tools, and it is about to meet real customers, some of them in regulated industries. You need someone to tell you plainly what could go wrong, what to fix first, and whether the platform choices behind it are sound.
What you get
- A plain-language list of what to fix first
- A second opinion on hosting, platform, and integration choices
- A record you can show a customer who asks about security
Policy. Platform. Proof. Applied to the application.
PolicyWhat secure means for this application
We map what data the application touches, how sensitive it is, and which obligations follow it. The output is a risk register the owner can read, not a scan dump.
PlatformWhether the architecture holds
Hosting and platform choices, authentication and access, where secrets and client data are stored, third-party services, and the permissions given to AI agents and integrations. For each choice we ask whether it was deliberate or a default.
ProofEvidence you can show
Prioritized findings in plain language and a written record of what was reviewed and when. Once fixes are made, an optional re-test confirms they worked.
Start shallow. Go deeper only if it is worth it.
Each step goes further into the application. The Snapshot is the entry point.
AI Application Security Assessment
Active testing, authorized in writing
Adds active testing, scoped and authorized before it begins, along with a full risk register, an architecture review, and a findings report suited to a vendor file or a customer security questionnaire.
Fractional AI Security Advisor
Ongoing, as scoped
Access as the application changes: architecture questions before they turn into rebuilds, review of new features and integrations, and periodic reassessment.
Remediation re-test
After fixes are made, we verify them. Scoped and quoted separately from the original engagement.
Hands-on implementation for founders
If you want fixes made rather than described, implementation is available as a separate service under its own agreement.
Every engagement is priced by scope, after a short scoping call. Reviews are point-in-time. They describe the application as we found it on the dates reviewed. They are not a certification and do not guarantee security.
We review it. We do not sell the platform.
No hosting, tooling, or licenses to sell, and no vendor quotas. Recommendations follow what your application needs.
The reviewer is a CISSP with 30 years securing sensitive data in regulated environments, 10+ years at Microsoft, and experience establishing AI governance frameworks for corporate use.
- Not a scanner reportAutomated tools produce long lists and no judgment. We start from how your application is built and what it protects, then use tools where they help.
- Architecture, not just codeWhich platform to choose, what to pay for, and where the application should live matter as much as any single vulnerability.
- Plain languageFindings are written for the person who has to decide, not only for the person who has to patch.
Questions people ask first
Is this a penetration test?
No. The Snapshot is a read-only review with no testing against a running application. Active testing begins at the Assessment tier and is scoped and authorized in writing before it starts.
Will you tell us the application is secure?
No, and be wary of anyone who will. We report what we found, what matters most, and what to do about it, as of the dates reviewed.
What do you need from us to start?
A short scoping call. We agree on what the application is, what data it touches, and what access, if any, you are comfortable granting. Nothing is installed or changed to begin.
Does it matter which AI tool built the application?
No. This applies to software built or assisted by any AI coding tool, and to AI features inside an application, such as agents, chat, and integrations.
Do you write the fixes?
Assessments describe what to change and in what order. For founders who want fixes made, hands-on implementation is available as a separate service under its own agreement.
We are an engineering team adding AI features to an existing product. Is this for us?
Our work centers on regulated firms and founders building with AI tools. If you are an engineering team, get in touch and we will tell you honestly whether we are the right fit.
Does my firm also need AI governance policy?
If you need a written AI policy, a tool inventory, and staff training for regulated client data, that is the core of our main practice. See AI risk and governance advisory.
Tell us what you are building or buying.
A short scoping call covers what the application is, what data it touches, and where you are in the build or the buying decision. We will tell you plainly which tier fits, or whether you need us at all.
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