How Code Authenticity and Scalability Reveal Hidden M&A Dealbreakers in Tech Due Diligence

Why Code Authenticity Is a Dealbreaker in M&A Due Diligence

Buying a tech company? Don’t skip the technical audit. I’ve sat across the table from founders, investors, and engineers on dozens of deals. One thing always stands out: the tech stack tells the real story.

Picture this: you’re about to close on a promising startup. Great revenue. Sharp team. Impressive pitch deck. Then, in the final stretch of technical due diligence, your engineer spots something off. The codebase has counterfeit components—copied code, sneaky licensing violations, or open-source software disguised as proprietary. It’s like buying a vintage watch that turns out to be a knockoff. The shell looks perfect. The gears are junk.

I’ve seen this ruin deals. In this post, I’ll show you how to expose code authenticity issues, test scalability risks, and run a technology risk analysis that exposes the truth behind the code — using real-world code quality audits and technical due diligence practices.

Code Authenticity: The Digital Counterfeit Problem

Counterfeit coins look real until you X-ray them. Same with code. I’ve audited startups where:

<
• Core features were copied from open-source projects with incompatible licenses (like GPL code in a closed-source SaaS).

<

• Code was “refactored” just enough to hide its source — but still broke under stress.

<

• Dependencies were outdated, unmaintained, or pulled from untrusted sources.

These aren’t edge cases. They’re common. And they can sink a deal fast.

How to Detect Code Authenticity in a Target’s Codebase

Start with a code provenance audit. Here’s how:

• SonarQube – catches code duplication, complexity, and quality issues.

<

• FOSSA or WhiteSource – maps open-source licenses and flags compliance risks.
• Git history analysis – reveals who wrote what, when. Look for ghost commits or bulk imports.

I once found a main.js file nearly identical to a popular React starter kit. The team swore it was original. But the Git log told a different story: one giant 10,000-line commit, two months before due diligence. No history. No evolution. Here’s what we found:

// In main.js
// Comments stripped, variables renamed — but logic unchanged
function handleUserOnboarding() {
  const u = getUser();
  const p = getPermissions(u);
  const m = merge(u, p);
  sendToAnalytics(m);
  return m;
}
// Same as the starter kit, minus the comments

That’s the digital version of an overstruck coin: polished on the outside, hollow inside. A red flag you can’t ignore.

Scalability Assessment: Can the Tech Stack Handle Growth?

Just because it works at 10,000 users doesn’t mean it’ll work at 100,000. I reviewed a fintech startup once. Beautiful interface. Stellar UX. But the backend? A single server. No caching. No load balancing. One database handling everything.

They looked ready to scale. They weren’t.

Key Scalability Red Flags

• No horizontal scaling – one server, one point of failure.
• High cyclomatic complexity – spaghetti code that’s hard to maintain or test.
• No observability – missing logs, monitoring, or tracing.
• Outdated database design – no sharding, no read replicas, no indexing.

Use a scalability assessment to stress-test the stack. My go-to checklist:

1. Load test – simulate 10x user growth with k6 or Locust.
2. Review architecture – look for microservices, containers, and automation.
3. Check database performance – slow queries? Missing indexes? Connection leaks?

One company claimed 500K monthly users. But at just 500 concurrent users, their API took over 5 seconds to respond. That’s not a product. That’s a time bomb. We passed on the deal.

Technology Risk Analysis: Beyond the Code

Code is only part of the story. Real technology risk analysis means asking: what happens if things go wrong?

• Technical debt – not just old code, but how hard it is to fix.
• Talent dependency – if one person built it, can others maintain it?
• Vendor lock-in – tied to one cloud, one tool, one API?
• Security gaps – unpatched libraries, open cloud buckets, weak authentication.

How to Conduct a Risk Scoring Matrix

I rate each risk with a 1–5 scale:

• 1 = Low risk (well-documented, automated, tested)
• 2 = Minimal concern
• 3 = Manageable (e.g., debt in a non-critical module)
• 4 = High risk (e.g., single point of failure in team or system)
• 5 = Critical (no backups, no CI/CD, no monitoring)

One company had clean code — but a 4/5 for talent dependency and 5/5 for security. One engineer knew the entire system. That’s not a tech risk. That’s a resignation risk. We flagged it immediately.

And don’t trust self-reported certs. I’ve seen startups claim SOC 2 compliance with zero proof. Always ask for: audit reports, penetration tests, third-party validation. Just like you’d verify a rare coin’s grading, verify the tech claims.

Actionable Takeaways: Your M&A Tech Due Diligence Checklist

Here’s what I do in every deal:

1. Run a Code Authenticity Audit

• Scan for open-source licenses with FOSSA.
• Study Git history — look for sudden, massive imports.
• Run SonarQube to find duplication and complexity.

2. Perform a Scalability Assessment

• Ask for architecture diagrams and past load testing reports.
• Confirm CI/CD pipelines and infrastructure as code.
• Check for auto-scaling and disaster recovery plans.

3. Conduct a Technology Risk Analysis

• Rate risks 1–5. Prioritize high scores.
• Verify security certifications and audit results.
• Assess team knowledge — not just headcount, but who knows what.

4. Validate Third-Party Claims

• Verify every certification. Don’t take screenshots as proof.
• Check for past red flags — bulk code imports, obfuscation, license violations.
• If something feels off, walk away. Integration costs and technical debt often cost more than the acquisition.

Don’t Get Duped by a Digital Counterfeit

In M&A, the tech is the real asset. A clean, scalable, original codebase? That’s a green light.

But hidden dependencies, fake code, or brittle architecture? That’s a red flag — no matter how slick the demo looks.

Like counterfeit coins that slipped past graders, bad code can fool smart investors. But with a solid code quality audit, scalability assessment, and technology risk analysis, you can spot the fakes before you sign.

Focus on three things: authenticity, scalability, and risk. Don’t judge a company by its website. Judge it by its code. And when you’re unsure — get a second opinion. Or walk away.

Related Resources

You might also find these related articles helpful:

• Building Better Cybersecurity Tools: Lessons from the Trenches of Threat Detection and Ethical Hacking – Ever wonder what separates the pros from the rest in cybersecurity? It’s not just tools—it’s *how* you build…
• Optimizing Supply Chain Software: Implementing Anti-Counterfeit Detection in Logistics and Warehouse Management Systems – Every dollar saved through smarter logistics software is a dollar earned. But today, efficiency isn’t just about speed o…
• Decoding High-End Game Performance: What Counterfeit Detection Teaches Us About AAA Game Optimization – Let me share something I learned the hard way: In AAA game development, raw power isn’t enough. I once spent three…