What a Security Audit Costs for an AI-Built Product

Ask four firms to audit the same AI-built SaaS app and the quotes will not cluster. You will get a free offer, something in the low thousands, something in the mid five figures, and a proposal that starts with "let's schedule a scoping call" and never names a number.

They are not pricing the same work. They are pricing different depths, different deliverables, and different levels of liability — and unless you know which you are buying, the numbers are not comparable at all.

This is what actually moves the price, what each tier gets you, and how to write a scope that makes quotes line up.

The five things that set the number

Surface area. Not lines of code — entry points. Count your API routes, background jobs, third-party integrations, database tables, storage buckets, and AI features that can call tools. An app with 20 routes and one integration is a different job from one with 120 routes and six.

Depth. Automated scanning is cheap because a machine does it. Manual code review costs senior engineering time. Adversarial testing of business logic — chaining legitimate actions into an exploit — costs the most because it is slow, skilled, and unautomatable.

Evidence requirements. An internal report you act on is one price. A report formatted to satisfy an enterprise buyer, an insurer, or an auditor, with an attestation letter and a retest, is another. Formality is a real cost, not a markup.

Whether fixes are included. Many quotes cover discovery only. Remediation is usually the larger number, because finding an open database table takes an hour and designing the right access model takes days.

Urgency. A two-week turnaround because a deal closes Friday costs more than a four-week slot. Everyone charges for this; not everyone says so.

What each tier buys

Two anchors worth holding onto. Industry-wide, rescue-and-harden engagements for AI-built apps typically run $1k to $15k over four to ten weeks — the audit is the front end of that, not a separate universe. And a first-year SOC 2 Type 2 for an AI startup lands around $40k to $120k, which tells you that if compliance is the real driver, the audit line item is a rounding error and should be scoped as part of the program. For the review-only breakdown, what an AI code audit costs goes deeper on that specific tier.

What you should receive for the money

Regardless of price, a real audit hands you artifacts you own:

• A findings list, each with severity, plain-English impact, the file or endpoint, and a concrete recommended fix.
• Evidence — a request, a screenshot, a reproduction step. Findings without evidence are opinions.
• A prioritization that distinguishes ship-blockers from cleanup, so you can plan work rather than panic.
• A walkthrough call where you can ask "how bad is this really" and get a straight answer.
• Clarity on scope: what was reviewed, what was not, and what the reviewer would look at next with more time.

If a quote does not describe those outputs, ask for a sample report with the client details removed. Every reputable firm has one.

Where money gets wasted

Paying an expert to find what a checklist finds. If nobody has looked at your app yet, run the pre-launch security checklist first. Exposed keys and open database tables are worth fixing at your own hourly rate, not at a consultancy's.

Buying depth you cannot act on. A 60-page report on a three-month-old app with no engineering team is shelfware. Buy the tier whose findings you can actually remediate inside a month.

Free audits with a sales attachment. A free scan that surfaces one obvious issue and pivots to a rebuild proposal is a lead magnet. Sometimes the rebuild is even the right answer — but you want that conclusion from someone who is not the only bidder, which is the argument in rebuild versus harden.

Open-ended hourly engagements. Without a defined deliverable, discovery expands to fill the budget. Fixed scope, fixed price, fixed report date.

Auditing a moving target. If your AI assistant is shipping features daily, findings go stale before you read them. Freeze the branch for the audit window.

How to write a scope that makes quotes comparable

Send every firm the same short brief:

1. Stack and hosting, in one line each.
2. Counts: API routes, database tables, integrations, AI features with tool access.
3. What data you hold, and whether any of it is health, payment, or EU personal data.
4. The driver: launch, enterprise deal, funding diligence, compliance, or an incident.
5. Whether you want discovery only, or discovery plus fixes.
6. Deadline and whether an attestation letter is required.
7. Access you can provide: repository, staging environment, test accounts at each role level.

Then ask each firm three questions: what is explicitly out of scope, who does the actual work and what is their background, and what does the retest cost. The answers separate serious proposals from templated ones faster than any price comparison.

Budgeting the fixes

Assume the fixes cost more than the finding, and plan for it up front rather than discovering it after the report lands. As a rough split for a small AI-built app, expect roughly a third of the total on discovery and two thirds on remediation and verification.

The good news is that the remediation is rarely a rewrite. In the engagements we run, the product logic and interface survive intact and the work is additive — move enforcement server-side, close the data layer, rotate credentials, add validation and limits, wire up tests. That is a scoped project with an end date, which is the whole argument for fixed-scope rescue work over open-ended retainers.

Frequently asked questions

How much should a pre-launch audit cost for an app built in a few weeks? For a small AI-built product with a handful of routes and one database, a focused audit with a written report typically lands in the $1k to $5k range. If a quote is dramatically higher, the firm is scoping something broader — usually formal testing or compliance evidence. Ask which.

Is an audit different from a pen test, and do I need both? Yes, and eventually. An audit reads the code and finds what exists; a pen test attacks the running app and proves what an outsider can reach. Audit first — it is cheaper and finds more per dollar in a generated codebase. Add a pen test when a contract or framework requires the letter.

Can I audit my own app to save money? The first pass, largely yes, and you should. Checklists cover the standard omissions well. What you cannot do alone is judge the findings you do not know to look for — access-control logic, the security of your AI tool wiring, and whether your architecture holds under a determined attacker. Do the free pass, then buy the expensive eyes for the part that needs them.

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If you are holding three quotes that differ by a factor of ten and cannot tell what you are actually buying, that is a scoping problem worth ten minutes of conversation. SprintX prices AI app security work as fixed-scope engagements with a written report you keep — send us your stack and your deadline.