Open source code is cheap to write but expensive to own. If you buy a SaaS with fragile dependencies, you inherit a haunted house. Here is how to spot the landmines before you sign the wire transfer.
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Most buyers approach a SaaS acquisition with one eye on the revenue and the other on the profit margin. They look at the MRR, check the churn rate, and if the numbers look green, they get excited. They rarely look under the hood. They don't ask who wrote the code, how it is structured, or what happens when the third-party library it relies on disappears. This is a massive blind spot. In the world of software, dependency management is where value goes to die. When you buy a SaaS, you are not just buying a user base; you are buying the code that serves that user base. If that code is built on a stack of unmaintained, open source dependencies, you are not buying a business. You are buying a ticking time bomb.
I have seen deals fall through not because of poor sales performance, but because technical due diligence revealed a fragile foundation. A SaaS might be generating $50,000 a month, but if the core authentication module relies on a deprecated Node.js package with no active maintainer, that valuation is an illusion. The moment you inherit that code, you become the maintainer. You inherit the bugs, the security holes, and the endless hours of rewriting code that should have been stable. The market value of a SaaS is heavily influenced by the technical health of the platform. A clean codebase with properly managed, supported dependencies commands a premium. A codebase riddled with "spaghetti" dependencies trades at a significant discount, or worse, fails to close entirely.
This post is for the serious buyer. It is for the person who understands that technical debt is a real liability, not just a buzzword. We are going to break down why open source dependencies are different from proprietary stack components, how they introduce unique risks, and most importantly, how to protect yourself during due diligence. If you are interested in finding high-quality acquisitions that avoid these pitfalls, you can explore vetted opportunities on Deal Alert AI where technical health is often a key part of the screening process. Let’s get into the specifics of what makes this risk so prevalent and how to navigate it.
When you build a modern SaaS, you are not writing every line of code from scratch. That would be impossible and inefficient. You are assembling a puzzle. You use React for the frontend, Node.js or Python for the backend, SQL or NoSQL for the database, and dozens of smaller libraries for specific tasks like date formatting, image processing, or API communication. These smaller libraries are your dependencies. In the open source world, a specific dependency is not just a chunk of code; it is a relationship with a maintainer or a community. If that relationship breaks, your product breaks. The risk is not that the code stops working immediately; the risk is that it stops working when you least expect it, often during a crisis when you do not have the time to fix it.
Consider the "left-pad" controversy or the recent npm supply chain attacks. These events highlighted a terrifying reality: the global software ecosystem is interconnected in ways that can cascade. If a core dependency is compromised or abandoned, every app using it is vulnerable. For a SaaS founder who built on these dependencies, it is a risk they may have accepted while bootstrapping. They relied on the community to keep the lights on. But when you acquire the business, you cannot rely on the community anymore. You are now a commercial entity. You need guarantees. You need stability. If the dependency is unmaintained, the community support is no longer a safety net; it is a hole in the floor of your business.
Furthermore, the "ecosystem effect" means that your competitors might be using the same dependencies. If you discover a fatal flaw or a security patch is needed for a popular library, you are in a race against other SaaS companies using the same library. If their engineering team is larger, or they hired a better consultant for due diligence, they will patch faster than you. Your brand suffers from the delay. Your customers notice the downtime or the missing features. In a highly competitive SaaS market, being the one who is slow to patch a common dependency issue is a reputational death sentence. You must view dependencies as active infrastructure, not passive code files.
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In proprietary software, if a developer quits, you can hire another one to take over their specific modules. The code is usually documented, internal, and self-contained. In an open source dependent SaaS, the "Bus Factor" is often zero for many components. The bus factor is the number of people who need to be hit by a bus before the project stops. For common open source libraries, if the maintainer gets busy, gets sick, or simply loses interest, the library dies. There is no HR department to fire them and replace them. There is no manager to give them a bonus to stay. There is only the silent drift of an abandoned GitHub repository. When you buy the SaaS, you are buying the responsibility to step into that void.
Let us look at a real-world example. Imagine a SaaS that uses a specific open source PDF generation library. This library has had one commit in two years. The last version has bugs that the community has reported in the issue tracker, but no one is responding. You buy the SaaS. Six months later, a major update to the operating system or the Docker container breaks the PDF generation. Your sales team can no longer send invoices. Your customers cannot download their reports. Your engineer looks at the source code and realizes they cannot easily patch it because the underlying logic is complex and undocumented. Now what? You spend $20,000 on an emergency consultant to rewrite the module from scratch. This was not in your operational budget. This was hidden in the technical debt of the acquisition.
This scenario is not hypothetical. It happens constantly in the M&A world. Buyers assume that because the software works today, it will work tomorrow. They do not account for the entropy of open source projects. Entropy is the natural tendency of systems to move from order to disorder. Without active maintenance, software degrades. This degradation is invisible until something breaks. The cost of fixing broken dependencies is always higher than the cost of managing them proactively. As a buyer, you must assume that any dependency without an active, recent release cycle is a liability that requires immediate replacement or heavy customization. This is a crucial distinction that separates a smart buyer from a naive one.
Open source is often associated with the word "free," but free code is never free. It comes with conditions. These conditions are known as licenses. The two most common licenses you will encounter are MIT/BSD and GPL (GNU General Public License). Understanding the difference is not just for lawyers; it is a core part of business strategy. MIT and BSD are "permissive" licenses. They allow you to use the code in any way you want, including in a commercial, closed-source product. They require you to cite the source, but that is it. They are safe for most SaaS acquisitions.
GPL, on the other hand, is a "copyleft" license. It contains a viral clause. If you use GPL code in your proprietary software, your entire software must often be released as open source under the same GPL license. For a SaaS, this is usually a disaster. You want your code to be a trade secret. You want to compete on your unique features, not on your open source repository. If a SaaS business has accidentally polluted its codebase with a GPL library, the entire business model may be at risk. The owner of the SaaS could be legally obligated to release their source code to the public, wiping out their competitive advantage and their valuation.
How does this happen? It happens through "dependency confusion." A developer uses a package that looks like a standard library. They do not read the license file. They integrate it deeply. By the time they prepare for sale, the legal team finds the GPL code buried in the stack. Now, the deal is paused. Lawyers scurry. The buyer demands a lower price or walks away. You must perform a Software Composition Analysis (SCA) before finalizing any offer. Tools exist to scan your codebase and identify every dependency and its license. If you see a GPL flag on a core component, treat it as a red alert. It is not a minor issue; it is an existential threat to the proprietary nature of the business.
In the past, you could secure your perimeter and be relatively safe. Today, the perimeter is everywhere, and that includes the code you import. A supply chain attack occurs when a hacker compromises a popular open source library. They inject malicious code into the library. Every company that updates to that version of the library downloads the malware. Because the library is trusted, the security walls let it in. This is how massive breaches happen. As a buyer, you are not just buying a company; you are buying its security posture. If the SaaS relies on a library with a history of vulnerabilities or one that is known to be a target for attackers, you are inheriting a security nightmare.
Consider the "Log4j" vulnerability that hit the Java ecosystem a few years ago. It was a critical flaw in a logging library used by thousands of enterprises. Companies scrambled to patch. Those who had documentation and knew exactly which version of Log4j they were using recovered quickly. Those who did not, who had forgotten which microservices relied on it, suffered extended downtime and potential breaches. If a SaaS target has poor documentation regarding its dependencies, you cannot trust their security. You do not know where the weak points are. You do not know if they are running outdated, vulnerable versions. This uncertainty must be factored into your valuation. a SaaS with a clean, up-to-date, and well-documented dependency tree is more secure and therefore more valuable than one with a dark, unknown history.
You must ask for the "Software Bill of Materials" (SBOM) if it exists. If it does not, ask for a list of all third-party libraries and their versions. Cross-reference these with the Common Vulnerabilities and Exposures (CVE) database. If you find critical CVEs associated with their dependencies, ask how they are mitigating them. If they are using a library that is no longer being patched for security, that is a daily risk. You are effectively running your business on sand. The next attack vector might simply be a library update that the SaaS team forgot to run. Proactive security depends on active dependency management. If the team is passive, you are at risk.
So, how do you actually check for these risks? You cannot do it by just looking at the dashboard. You need to go into the code. You need to look at the *package.json* file (for Node.js), the *requirements.txt* (for Python), or the *pom.xml* (for Java). These files list the dependencies. Look at the versions. Are they locked to specific versions? Or are they using wildcards (like `*` or `^`)? Wildcards are dangerous in production. They mean the developer does not care about stability. They let the package manager decide which version to install. This can cause breakage without warning. Look for long lists of dependencies. A "lean" codebase is valuable. A "bloated" codebase is a burden.
You must also look at the GitHub repository of the SaaS itself. Check the commit history. Are there commits that say "update library" or "fix dependency conflict"? If these commits are rare, it means they are not actively managing their dependencies. If they are frequent and chaotic, it means the system is fragile. Talk to the engineering lead (if there is one) or the founder. Ask them: "If I break a dependency today, how long does it take to fix it?" A good team will have a backup plan. They will know which parts of the code are decoupled from specific libraries. A bad team will panic. They will say "we usually hope it doesn't break." That is a red flag.
Use automated tools as a first pass, but always follow up with manual review. There are CI/CD pipelines that can scan for vulnerabilities. Ask to see the output of these scans. If the scan is not running, ask why. Lack of automated dependency scanning is a sign of cultural technical debt. It means the team is reactive, not proactive. You are buying a reactive team. You will have to spend time and money to change that culture. Factor that into your price. A SaaS with a proactive engineering culture and clean dependency management is worth a premium because it is a smoother ride. A SaaS with a passive culture is a discount opportunity, but only if you have the skills to fix it.
To help you navigate this complex landscape, I have compiled a practical checklist you can use during your due diligence phase. This is not just a list of questions; it is a framework for risk assessment. Use it for every deal you review. It will help you spot the hidden costs that are not on the balance sheet. It will help you negotiate a better price based on technical reality, not wishful thinking. If you are new to this, this checklist is your shield. It gives you the language to ask the hard questions. It gives you the data to back up your claims. Do not skip it.
This checklist is comprehensive, but it is not exhaustive. Every SaaS is different. A data-heavy SaaS has different risks than a text-heavy SaaS. Adapt these steps to the specific technology stack of your target. The goal is not to find a perfect SaaS; it is to find a SaaS with known, manageable risks. Unknown risks are the enemy. Known risks can be priced. Manageable risks can be fixed. By using this checklist, you convert the unknown into the known. You gain leverage. You gain confidence. You turn a risky purchase into a calculated investment.
Finding a SaaS with a clean technical foundation takes work. Most brokers and marketplaces do not prioritize technical due diligence. They focus on the financials. This is a gap in the market. But there are places that do better. Marketplaces that vet the technical health of the businesses are becoming more common, and you should prioritize them. When you look for a SaaS, look for listings that explicitly mention their tech stack and their maintenance practices. Transparency is a good sign. If a seller is open about their code, they are often more honest about their business.
Platforms like Empire Flippers and Flippa offer a wide range of opportunities. While they are general marketplaces, they often have strong due diligence processes for higher-value deals. However, you must still do your own technical homework. The marketplace listing is the starting point, not the end point. Use the data from these platforms to build your initial shortlist, then dive deep into the technical stack as described above. Do not rely on the brokerage to check the GitHub repositories for you. They may check for revenue fraud, but they rarely check for dependency rot. You must be your own technical auditor.
For those who want a more curated experience, Deal Alert AI is a platform that leverages data to help buyers identify opportunities with less noise. While not every SaaS is perfect, the goal is to help you find businesses that are built on solid ground. The future of SaaS acquisitions will be dominated by buyers who understand the technical details. As AI and automation continue to change the coding landscape, the importance of dependency management will only grow. The code will get more complex. The libraries will become more intertwined. The risk will increase. But for the buyer who prepares, the risk is also the opportunity. You can buy a slightly underperforming SaaS with a messy codebase, fix the dependencies, and increase its value significantly. That is the alpha. That is the real profit. The valuation is not in the current code; it is in the work you are willing to do to make it robust.
Buying a SaaS is a serious business decision. It requires a blend of financial acumen and technical literacy. You do not need to be a programmer, but you need to be a technical detective. You need to know what to look for. You need to know how to ask the right questions. The open source ecosystem is the backbone of the modern web. It gives us tools, speed, and efficiency. But it also gives us vulnerability, complexity, and uncertainty. The key is to manage that uncertainty. To turn it into a controllable variable. To price it in. To fix it when necessary.
As you move forward with your search, keep this mindset. Look past the revenue. Look at the foundation. A house with a beautiful interior but a cracked foundation is not a safe place to live. The same applies to SaaS. The MRR is the interior. The code is the foundation. If the foundation is made of crumbling bricks (unmaintained dependencies), the interior does not matter. Crack a brick, and the whole wall might fall. Your due diligence must be thorough. Your questions must be sharp. Your expectations must be realistic. The market is full of deals. Some are great. Some are traps. The difference is you. Your knowledge. Your preparation. Use the tools, do the homework, and protect your investment.]
Remember, the goal is not to avoid open source; open source is essential. The goal is to avoid unmanaged open source. Manage it, document it, secure it, and it becomes an asset. Neglect it, and it becomes a liability. As a buyer, you have the power to choose. Choose the SaaS with the clean stack. Choose the seller with the transparent practices. Choose the deal that lets you sleep at night. That is how you build a portfolio of profitable, sustainable businesses. That is how you win in the SaaS market. Good luck.
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