How Much Does a Code Audit Cost? (Real Pricing Breakdown)

We audit codebases for a living. Founders ask us how much it costs before every other question. Fair enough. You’re running a company, not browsing a menu for fun.

Most audit firms don’t publish pricing. They want you on a call first so they can “scope the engagement” — which usually means sizing up your budget. We think that’s backwards. You should know what you’re walking into before you talk to anyone.

So here’s what code audits actually cost, what makes the price move, and how to tell if you’re getting a real review or an expensive PDF.

The pricing tiers

Not all audits are the same engagement. The scope determines the price, and the scope depends on what you need to know and who’s going to read the output.

Automated scan only: Free to $500

This is the entry point. Automated tools run static analysis across your codebase — checking for known vulnerabilities, dependency issues, secret leaks, and structural problems. No human reads your code.

We built a free automated audit tool that does exactly this. It runs seven analyzers and gives you a structured report in minutes. Other firms charge $300–$500 for essentially the same thing with a branded cover page.

Good for: getting a baseline, catching low-hanging fruit, deciding if you need a deeper review.

Not good for: understanding architecture decisions, evaluating scalability, or anything that requires judgment. Automated tools find what they’re programmed to find. They don’t understand your business context.

Focused audit: $2,000–$5,000

A senior engineer reviews your codebase with a specific lens — security, performance, architecture, or data model. The scope is narrow by design. You’re not asking “is this code good?” You’re asking “will this authentication system hold up?” or “why does this page take four seconds to load?”

Typical timeline: 3–5 days of review, followed by a written report with prioritized findings.

Good for: answering a specific question, pre-launch security checks, investigating a known problem area.

We ran a focused security audit last month for a fintech startup — 14K lines of code, Node.js and PostgreSQL. Three days of review. Found two critical auth bypass vulnerabilities and a race condition in their payment flow that would have let users double-spend credits. The $3,500 they spent saved them from a breach that would have ended the company before Series A.

Comprehensive audit: $5,000–$10,000

This is the full review. Every significant file gets read by a human. We evaluate architecture, security, code quality, test coverage, dependency health, error handling, data modeling, and scalability. The output is a detailed report with findings categorized by severity, plus a prioritized remediation plan with effort estimates.

Typical timeline: 1–2 weeks depending on codebase size.

Good for: founders preparing to scale, teams inheriting a codebase, CTOs who need an honest external assessment, anyone who built with AI tools and wants to know what’s actually in there.

Most of our engagements land here. A SaaS founder with a 20K LOC codebase, growing fast, wondering if the foundation will hold. The answer is usually “mostly, but here are the three things that will break first.” That’s worth knowing before you hire five engineers and point them at the wrong problems.

Investment-grade due diligence: $10,000–$20,000+

This is a different deliverable entirely. The audience isn’t your engineering team — it’s investors, acquirers, or a board. The report needs to withstand scrutiny from people making million-dollar decisions based on what it says.

We cover architecture, security, scalability, team assessment, IP/licensing, technical debt quantification, and an honest evaluation of the technology as a business asset. The report includes risk ratings, remediation cost estimates in engineering-weeks, and clear language that non-technical stakeholders can act on.

Typical timeline: 2–4 weeks. Often includes interviews with the engineering team.

Good for: pre-acquisition technical due diligence, fundraising preparation (especially Series B+), PE firms evaluating software assets, acqui-hire assessments.

A PE firm hired us to review a SaaS platform they were acquiring for $8M. We found that the “microservices architecture” described in the pitch deck was a monolith deployed three times, the test suite hadn’t passed in four months, and 40% of the codebase was AI-generated with no review process. They renegotiated the price down by $1.2M based on remediation estimates from our report. Our fee was $18K.

What drives the cost

Same engagement type, different price. Here’s why.

Codebase size. A 5K LOC MVP and a 80K LOC platform are different animals. More code means more reading time, and reading is the expensive part. We scope by LOC as a starting point, but size alone doesn’t tell the full story.

Number of languages and frameworks. A Next.js monorepo is one thing. A system with a Python ML pipeline, a Go API, a React frontend, and Terraform infrastructure is four things. Each language requires a reviewer who actually knows it. Polyglot systems cost more because they require more specialized time.

Urgency. Our standard timeline is 1–2 weeks for a comprehensive audit. If you need it in 3 days because you’re closing a deal next week, that’s a rush engagement. Expect a 30–50% premium. We’ve done 48-hour turnarounds for active M&A deals, but we charge accordingly because it means dropping everything else.

Scope. Security-only is cheaper than security-plus-architecture-plus-scalability-plus-data-modeling. The more questions you need answered, the more time it takes. Some clients start with a focused audit and upgrade to comprehensive after the initial findings.

Deliverable audience. An internal report for your engineering team is a different document than an investor-facing assessment. The latter needs more careful language, executive summaries, risk quantification, and often multiple rounds of review. That editing and formatting time is real work.

AI-generated code. This is increasingly a factor. Codebases built primarily with AI tools — Cursor, Claude Code, Copilot, Bolt, Lovable — require a different kind of attention. The code looks clean. The patterns are consistent. The problems hide under that surface. We’ve written extensively about what we find in AI-generated codebases, and reviewing them takes longer because you can’t trust the code’s apparent quality. If your codebase needs cleanup after AI-assisted development, that’s a separate engagement — we offer vibe code cleanup specifically for this.

What you’re actually paying for

An automated scan gives you a list of issues. A human audit gives you understanding.

When a senior engineer reads your codebase, they’re not just looking for bugs. They’re evaluating whether your data model will survive 10x growth. Whether your authentication approach will pass a SOC 2 audit. Whether the abstractions your team built will help the next five engineers or slow them down. Whether the shortcuts you took to ship fast are the kind you can clean up later or the kind that require a rewrite.

You’re paying for judgment. AI tools can scan code faster than any human. They can find known vulnerability patterns, flag dependency issues, and check for common anti-patterns. What they can’t do is evaluate whether your architectural decisions make sense for your specific business, your specific growth trajectory, and your specific team. They can’t tell you that your caching strategy works fine now but will create a consistency nightmare when you add a second data center. They can’t tell you that your payment integration handles the happy path perfectly but will lose money on every failed partial refund.

You’re paying for someone who has seen fifty codebases like yours and knows which problems actually matter.

When to get a code audit

Before fundraising. Sophisticated investors will ask about your technical foundation. Having a third-party audit on hand, especially one that shows you’ve addressed the findings, signals maturity. We’ve seen it directly accelerate due diligence timelines.

Before an acquisition. Whether you’re buying or selling. Buyers need to know what they’re getting. Sellers who provide a clean audit report get better terms because they’ve removed uncertainty from the deal. We have a full guide on pre-acquisition code review if this is your situation.

Before scaling. You’re about to hire three engineers and 3x your feature velocity. If the foundation has cracks, you’re about to build on top of them at speed. It’s cheaper to find out now.

After building with AI tools. You shipped fast with Cursor or Claude Code or Bolt. The product works. Users are happy. But you have no idea what’s actually in the codebase because you didn’t write most of it. This is increasingly the most common reason people come to us.

Before compliance reviews. SOC 2, HIPAA, PCI — the auditors are coming, and they will find things. Better to find them yourself first and fix them on your own timeline.

Red flags in audit pricing

Not all audit providers are doing the same work. Here’s how to tell.

Anyone who quotes a firm price without seeing the codebase is guessing. We give ranges upfront (like this article), but a real quote requires at least a brief look at the repo — the size, the stack, the complexity. A firm that says “$4,000, flat rate, any codebase” is either cutting corners or padding the price for small projects.

Per-line pricing is nonsense. “We charge $0.10 per line of code” sounds precise. It’s not. A 50K LOC codebase with clean architecture and one language is simpler to review than a 15K LOC codebase with four languages, no tests, and spaghetti dependencies. Lines of code are a scoping input, not a pricing formula.

If it takes two days for a 50K LOC codebase, they’re not reading it. They’re running automated tools and writing a summary. That has value — it’s the $500 tier. But if they’re charging $8,000 for two days of work on a large codebase, you’re paying human-review prices for automated-scan output.

“Comprehensive audit” with no mention of architecture or data modeling. If the deliverable is just a list of security vulnerabilities and dependency versions, that’s a security scan, not a code audit. Scans are useful. They’re not the same thing.

No sample report available. A firm that does this regularly should be able to show you a redacted example of their output. If they can’t, they either don’t do many audits or the output isn’t structured enough to share.

What a good audit report looks like

You should get more than a list of problems. A useful audit report includes:

• Executive summary — what’s the overall health, in plain language
• Findings by severity — critical, warning, informational, with specific file references
• Architecture assessment — not just “is the code clean” but “will this scale”
• Prioritized remediation plan — what to fix first, estimated effort for each item
• Positive findings — what’s done well, so you don’t accidentally break the things that work

The report should be actionable the day you receive it. If your team can’t start fixing things immediately based on what’s in the document, the audit didn’t do its job.

Get started

We offer a free AI Code Health Check — five questions, two minutes, and you’ll get an initial assessment of where your codebase stands. It’s not a substitute for a human review, but it tells you whether one is worth the investment.

Start your free Code Health Check here.

If you already know you need a full audit, reach out through the same page. We’ll look at your repo, give you a real scope and timeline, and tell you exactly what it’ll cost before you commit to anything.