Startup codebases tell a story. Built under pressure, with limited resources, and often by small teams wearing multiple hats, they reflect the compromises that were made to get a product to market. Some of those compromises are reasonable and manageable. Others are structural problems that will cost significantly more to fix post-close than they would have to identify pre-close.

Knowing which is which requires direct access to the codebase and the expertise to read what you find there. Here are the most common red flags — and what each one tells you about the risk you are taking on.

Red Flag 1: No Automated Testing

Low or absent test coverage is one of the clearest indicators of a codebase that will be expensive and risky to change. When there are no automated tests, every modification to the platform is a leap of faith. Engineers cannot refactor with confidence, cannot deploy without manual regression testing, and cannot onboard new team members without significant knowledge transfer overhead.

In a startup context, skipping tests is understandable — the pressure to ship fast is real. But a business approaching acquisition with no meaningful test coverage has made a choice that the acquirer will pay for. The remediation cost — building a test suite retrospectively across a mature codebase — is substantial, and the risk during the interim period is real.

Red Flag 2: Outdated or Abandoned Dependencies

Modern software is built on dependencies — third-party libraries, frameworks, and packages that handle common functions. These dependencies are only as reliable as their maintenance status. Libraries that are no longer actively maintained stop receiving security patches, stop being compatible with newer system components, and eventually become a constraint on the platform’s ability to evolve.

A startup codebase with a significant proportion of outdated or end-of-life dependencies is carrying a known, quantifiable liability. It is also carrying an unknown one: unpatched CVEs (Common Vulnerabilities and Exposures) that may already be publicly documented and actively exploited. Dependency scanning is one of the fastest and most revealing elements of any codebase assessment.

Red Flag 3: Hardcoded Credentials and Secrets

Few findings in a codebase assessment are as immediately alarming as hardcoded credentials — API keys, database passwords, authentication tokens — embedded directly in the code rather than managed through a secrets management system. This is a critical security failure that exposes the platform to immediate compromise if the codebase is ever accessed by an unauthorised party.

It is also more common in startup codebases than most acquirers expect. Early-stage development frequently prioritises speed over security hygiene, and secrets management is often deferred until “later” — which, in many cases, means never. The presence of hardcoded credentials is not just a security red flag. It is an indicator of the overall security culture within the engineering team.

Red Flag 4: Monolithic Architecture with No API Layer

A tightly coupled monolithic architecture with no clean API layer creates three compounding problems for an acquirer. First, it limits scalability — the entire system must scale as a unit, regardless of which components are under load. Second, it creates fragility — changes to one component risk breaking others in ways that are difficult to predict or test. Third, it makes integration dramatically more complex and expensive — a critical issue for acquirers with a platform or buy-and-build strategy.

The absence of an API layer is particularly telling. It signals that the platform was never designed to integrate with anything external — a significant constraint for any acquirer whose value creation plan involves connecting the acquired product to an existing portfolio or customer base.

Red Flag 5: Undocumented Business Logic

Documentation debt is one of the most consistently underestimated risk factors in startup codebase assessments. When business rules, integration logic, and architectural decisions exist only in the minds of one or two engineers — rather than in documentation or self-explanatory code — the acquirer is not just buying a platform. They are buying a dependency on specific people to explain how it works.

When those people leave — and in the post-acquisition period, some always do — the knowledge leaves with them. Maintenance becomes more expensive, onboarding takes longer, and the risk of introducing defects through misunderstood logic increases. Undocumented codebases are not just a quality issue. They are an operational continuity risk.

Red Flag 6: Security Architecture as an Afterthought

In many startup codebases, security was not designed in — it was bolted on. The symptoms are recognisable: authentication that was added after the initial build, access controls that are inconsistent across the platform, encryption that was implemented partially or incorrectly, and compliance requirements that were addressed through documentation rather than technical controls.

This pattern is particularly dangerous in regulated sectors. A SaaS platform handling financial data, health records, or personal information that has not been built with security as a first principle is carrying a regulatory liability that transfers unconditionally to the acquirer at close. Under the EU AI Act, GDPR, and sector-specific frameworks, the penalties for non-compliance are significant — and the cost of retrofitting genuine security controls into an insecure codebase is typically far higher than the cost of building them in from the start.

Specific red flags to look for include: absent or inconsistent input validation, missing rate limiting on public-facing APIs, weak or reused encryption keys, absence of audit logging, and role-based access controls that exist in name only.

Red Flag 7: AI-Generated Code Without Governance

As AI coding assistants — GitHub Copilot, Cursor, Claude — become standard tools in engineering teams, a new category of codebase risk has emerged: AI-generated code that has not been adequately reviewed, tested, or understood by the engineers who shipped it.

AI-generated code can introduce subtle bugs, security vulnerabilities, and licensing complications that are not visible through standard code review. Code generated from training data that includes proprietary or GPL-licensed material can create IP exposure that is difficult to quantify and expensive to remediate. And a codebase where a significant proportion of the logic was generated rather than written by the team raises fundamental questions about maintainability — can the engineering team explain, modify, and extend what exists, or are they working in code they do not fully understand?

The right question in a modern startup codebase assessment is not just “what was written?” but “how was it written, and by whom?”

What These Red Flags Tell You

No startup codebase is perfect. The goal of a codebase assessment is not to find a reason to walk away — it is to understand what you are actually acquiring and what it will cost to bring it to the standard the acquirer’s plans require.

Each red flag has a commercial implication: a remediation cost, a timeline impact, or a risk that needs to be addressed through deal structuring. Quantifying those implications — and translating them into deal terms — is the core of what rigorous technology due diligence delivers.

At VeryDiligent, our codebase assessments are conducted by experienced engineers who know what to look for and how to translate what they find into commercial terms. We give investors and acquirers the clarity they need to make confident decisions — and to negotiate deals that reflect the true risk profile of what they are buying.

Contact us today to discuss your upcoming transaction.

Related reading: The Hidden Technical Debt That Kills Post-Acquisition Value | What Questions to Ask a CTO During Due Diligence | Cybersecurity Due Diligence: The New Dealbreaker