If an App Is Open Source, Does That Actually Make It More Private?

I often see open source platforms being spoken about with a great deal of trust, particularly when “privacy and security” are part of the conversation. And that trust is understandable. But I wanted to look at the subject from a broader privacy perspective.

Does making an app’s source code publicly available automatically make it more private? Or is there more to privacy than simply being able to see the code?

This is clearly not an open source vs. closed source or which is better CONTENT.

No!

This is not an argument against open source, nor an attempt to take sides in the open source versus closed source debate.

It is a perspective informed by research, and a closer look at what transparency can and cannot guarantee.

Open source is valuable because it makes independent scrutiny possible. But visibility alone does not guarantee that code is reviewed, vulnerabilities are responsibly handled, or users’ privacy is protected.

The intention here is not to challenge the open source philosophy, but to examine the gap between what openness makes possible and what actually happens in practice.

I would say this is my point of view on this discussion,

First, not everyone is technically informed enough to make decisions and understand reviews.

Open source has become one of the most frequently cited arguments in discussions about digital privacy, chat applications, encrypted messaging apps, particularly when people compare messaging applications, browsers, operating systems, and other tools that handle personal information.

Yes, it has influence and credibility, no doubt.

The reasoning is that if developers make their source code publicly available, anyone can examine it, identify weaknesses, challenge questionable decisions, and verify what the software actually does.

And that is a meaningful advantage.

So here I would add my two cents which clearly are not against or favor stuff.

1. Making software possible to inspect is not the same as having it independently inspected.

2. Being open source also does not mean all aspects of an app are secure, and there could be no potential risks.

3. If an app’s code is public, surely someone can spot anything suspicious. But what happens when nobody is actually checking, fixing, or managing the security problems?

4. Not everyone has the technical knowledge to examine a repository, understand cryptographic implementations, follow software dependencies, or investigate how an application handles information behind the scenes.

Most people make decisions using the information available to them: privacy policies, security features, permissions, independent reviews, and the reputation of the company or development team.

Yes, no doubt, when an application is open source, another reassuring detail is added to the list.

But do all the people using the platform actually examine its repository, follow its dependencies, inspect its network requests, or compare the application available for download with the code published by its developers?

Many users would not even know where to begin, and what are these terms even?

This does not make open source less valuable. It means we need to understand what it actually provides.

“Transparency, independent verification, security, and privacy” are connected, but they are not interchangeable.

A public repository can tell us a great deal about how software is designed, but it does not automatically answer every question about how that software is developed, distributed, maintained, or operated.

Also, a large community does not necessarily mean a large security-review team.

The number of GitHub stars does not tell us how many people have examined an application’s encryption. The number of downloads does not establish that its authentication system has been independently tested. And a large contributor community does not guarantee that someone is monitoring every security-sensitive change.

The advantage of open source is the opportunity for more people to participate in examining software.

Just because the code is visible doesn’t mean someone is protecting it.

One of the biggest arguments in favor of open-source software is transparency. Anyone can examine the code, identify weaknesses, and potentially report security problems.

But something we often overlook is that making code available for inspection and actually inspecting it are two very different things.

Vulnerability can exist in publicly available code for months. Someone might discover it, but if the developers don’t know about it, don’t respond, or don’t have the resources to fix it, the problem remains.

I would mention some points from a 2025 study published by ACM that examined 8,073 open-source projects and analyzed 21,501 reported vulnerabilities associated with GitHub.

One of its findings is that 60% of the examined projects lacked both a clearly defined security policy and a private way to report vulnerabilities.

Think about what that means.

The code may be open for everyone to see, but when someone discovers a security weakness, there may not even be a clear place to report it privately.

Transparency creates the opportunity for security improvements. It does not guarantee that those improvements will happen or have happened after information.

Again, these figures do not prove that open-source software is inherently less secure. They describe the projects and vulnerabilities included in that particular study.

(Don’t just think about that one messenger because there are many platforms)

What they explain is something more specific: public code does not automatically produce mature security practices, responsible disclosure procedures, or effective vulnerability management.

A project can be transparent about its source code and still have weaknesses in the way it responds to security problems.

In such cases, independent security research also matters. A proper review should examine specific implementation decisions, investigate potential attack surfaces, assess how sensitive information moves through the application, and explain the scope and limitations of its findings.

Transparency has a side that people rarely discuss.

Can making vulnerabilities public pose additional risks?

This is another area where the discussion needs balance.

When a vulnerability is discovered in open-source software, the information may eventually become publicly available. That transparency can help developers, researchers, and users understand the problem and verify whether a fix addresses it.

But vulnerability information can also help attackers understand where a weakness exists.

This is not an issue exclusive to open source. Vulnerabilities in proprietary applications can also become public through security advisories, research publications, exploit databases, or incidents in which attackers discover weaknesses before a patch is available.

The important factor is how the vulnerability is handled.

Responsible disclosure practices allow developersto investigate reported issues, prepare fixes, and coordinate communication with researchers before technical details are widely published.

A project should ideally provide a clear security policy, a private reporting channel, a process for acknowledging reports, and a way to communicate patches and advisories.

Without those practices, public availability of source code does not necessarily translate into a responsible security response.

The ACM research discussed earlier is relevant here. Its findings about missing vulnerability-handling information and public discussions before formal disclosure show why security management deserves as much attention as code availability.

Transparency is valuable. So is giving developers a reasonable opportunity to address a vulnerability before its details become a practical guide for exploiting it.

Neither should be treated as an argument against open source. They are reasons to evaluate how a project manages security throughout its development lifecycle.

Open-source software encourages people to share information, discuss problems, and contribute improvements. That openness is valuable, but security vulnerabilities require a little more care.

Imagine someone discovers a weakness in an application. If they immediately describe it in a public GitHub discussion, developers and users can see the problem.

Unfortunately, attackers can see it too.

The research found that approximately 42% of the studied vulnerabilities had been discussed publicly in GitHub issue reports before their official disclosure.

This creates a difficult situation.

Who takes responsibility when something goes wrong?

An open-source application can have thousands of users, contributors, and people who can access its code. But that doesn’t necessarily mean it has a dedicated security team.

Some projects have limited developers, fewer resources, or very little ongoing maintenance.

The research also found that vulnerabilities publicly reported in smaller and less active projects were often left unresolved.

This raises an important question for anyone choosing an open-source application:

If a security problem is discovered tomorrow, who will fix it?

The existence of a public repository does not answer that question. What matters is whether someone actively maintains the application, responds to security reports, and releases updates when problems are discovered.

An application can be open source and still have security problems that nobody is actively addressing.

Good intentions are not the same as good security practices.

The researchers surveyed 770 software practitioners to understand how they believe security vulnerabilities should be handled.

More than 81% preferred a process called Coordinated Vulnerability Disclosure (CVD).

In simple terms, this means a security researcher privately informs the developers about a vulnerability, allowing them to prepare a fix before the details become public.

But when researchers examined what actually happened across open-source projects, they found a gap between what developers preferred and what projects practiced.

Only 56% of the studied vulnerabilities followed a disclosure process similar to coordinated disclosure.

In other words, supporting a responsible security process and consistently following one are two different things.

For users, this distinction matters. An application’s security depends not only on the principles its developers believe in, but also on the systems and actions they put into practice.

These are findings from the above research going forward.

The application you download is not necessarily the code you inspected

This is another technical issue when discussing open-source applications.

When developers publish source code, they are publishing the material from which software can be built. What users eventually download is a compiled application, commonly called a binary.

These are related, but their relationship is not automatically verified.

Consider a hypothetical situation in which an application publishes its source code on GitHub, but the version distributed through an app store contains a modified component, an additional library, or a different configuration.

Someone inspecting the public repository might find nothing suspicious because the questionable change is not present in the code they examined.

This does not mean developers routinely manipulate their releases. It means there is a technical gap between publishing source code and demonstrating that the distributed application corresponds to it.

This is precisely why reproducible builds matter.

A reproducible build allows independent parties to compile an application using the published source code and specified build environment, then compare the resulting output against the developer’s released application.

When the builds match, there is stronger evidence that the distributed application corresponds to the publicly available source code. When they do not, the differences require investigation.

The F-Droid documentation on reproducible builds explains how this works for Android applications, including the verification of APKs and the practical challenges involved in producing identical builds.

I particularly value this approach because it moves the discussion beyond what a developer says is happening and towards something another party can attempt to verify independently.

There is a difference between being told that an application is built from public source code and having evidence that its released version can actually be reproduced from that source.

For privacy-conscious users, that difference should not be overlooked.

What about the parts of an application that are not open source?

An application is rarely a single, self-contained piece of software. Modern applications depend on external libraries, software development kits, analytics services, push notification systems, cloud infrastructure, and sometimes third-party APIs.

Each component can introduce its own security and privacy considerations.

A developer might publish the main application code while relying on external components whose internal implementation is not publicly available.

Consider an analytics SDK integrated into an otherwise transparent private messaging application. You might be able to inspect the application’s code and identify where the SDK is initialized, but you may not have equivalent visibility into everything the external service collects, processes, or transmits.

The same concern applies to crash-reporting tools, advertising frameworks, third-party authentication services, and cloud-based infrastructure.

This raises an important question that how much of the application are we actually examining when we call it open source?

The answer depends on its architecture and dependencies.

Software Composition Analysis, commonly known as SCA, helps developers identify third-party components, their versions, and known vulnerabilities. Software bills of materials, or SBOMs, provide another way of documenting the components included in a software product.

Neither mechanism independently proves that an application respects privacy. Knowing which libraries an application uses does not automatically tell us what information those libraries process or whether their behavior is appropriate.

However, both practices improve visibility into the software supply chain.

1. The OpenSSF Scorecard is another useful resource. It evaluates open-source projects against automated security checks, including aspects of maintenance, development practices, and security hygiene.

These tools introduce more meaningful questions than simply asking whether a repository is public.

Who maintains the dependencies? Are they regularly updated? Are known vulnerabilities monitored? Is there a process for replacing compromised components? Does the project document the software included in its releases?

These questions deserve answers regardless of whether an application’s source code is available.

Public source code does not automatically reveal what happens on the server

This is particularly important when evaluating messaging applications, cloud services, and other platforms that depend on centralized infrastructure.

Users interact with an entire service, not just the application installed on their devices.

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A messaging application might publish its client-side code while keeping its server-side implementation private.

In that situation, researchers can examine how the application behaves on a device, but they may not be able to inspect the complete system responsible for processing account information, delivering messages, or managing other operational data.

Even when both client and server code are available, another question remains: is the deployed service actually running the published version?

A public repository does not, by itself, establish what is happening inside a company’s production environment.

For example, a developer might publish code explaining how a service handles certain information, but users still need evidence about how the actual infrastructure is configured, who has access to it, and how operational policies are enforced.

There are several questions worth considering:

1. Is the server-side code publicly available?

2. What information does the service process when users connect?

3. Are connection logs or other operational records retained?

4. Who has administrative access to the infrastructure?

5. Can independent parties verify important claims about the deployed service?

This does not mean that every service must publish its entire infrastructure to demonstrate responsible data handling. There are legitimate operational and security considerations involved.

It means that we should not assume public application code provides complete visibility into everything happening behind the service.

For messaging platforms in particular, this distinction matters because end-to-end encryption, metadata handling, account management, and server-side data retention involve different parts of the architecture.

Understanding one does not automatically establish the others.

Who controls the updates you receive?

Another point worth considering is how software changes after its source code becomes public.

An open-source application may have a publicly accessible repository, but most users install updates through an official website, an application store, or an automatic update mechanism.

They do not personally examine every change before installing it.

Developers and maintainers control the release process. They can introduce new functionality, modify existing behaviour, update dependencies, and change the way particular components operate.

This is normal software development. Applications need updates to fix bugs, improve performance, introduce features, and address security problems.

But it also raises an important question: how much can users verify about the updates they receive?

A project’s public development history can help researchers examine changes. Signed releases can help establish the authenticity of software packages. Reproducible builds can provide evidence connecting distributed binaries to published source code.

Code review and protected development processes can also reduce the likelihood of unauthorized changes entering official releases.

These mechanisms serve different purposes, but together they contribute to a more trustworthy release process.

The important point is that open source does not remove the need to evaluate how software is updated and distributed. Transparency should extend beyond the original repository to the way users actually receive the application.

What happens to information after it reaches the service?

This is one of the most important questions in any privacy discussion, and it deserves attention regardless of whether software is open source or proprietary.

An application might have excellent encryption and a transparent codebase, but what happens when information reaches its servers?

Consider the information surrounding an ordinary messaging account:

• Account identifiers and registration details.
• IP addresses and connection metadata.
• Device and diagnostic information.
• Usage analytics.
• Message delivery information.
• Data retention and deletion.
• Information shared with third-party service providers.

These categories are not interchangeable. A platform may need certain operational information to provide its service, while other forms of collection may be optional or unnecessary.

The question is not simply whether an application collects data. It is what information is collected, why it is needed, how long it is retained, and who can access it.

An open-source repository can help researchers investigate what the application is designed to do.

It cannot, on its own, establish that the organization consistently follows its published retention policy or that internal access controls are being enforced correctly.

For example, a privacy policy might state that certain information is deleted after a defined period. The existence of publicly available application code does not independently prove that deletion happens as described across the company’s actual infrastructure.

This is where other forms of evidence become important: clear data-handling documentation, independent assessments, appropriate operational controls, and transparent explanations of retention practices.

What happens when an open-source project is no longer maintained?

There is another practical consideration

A project can have a strong technical foundation, a public repository, and a history of useful contributions, yet become increasingly difficult to trust if its maintenance stops.

Software does not remain secure simply because its original code was well written.

Operating systems change. Dependencies develop new vulnerabilities. New attack techniques emerge. Application environments evolve, and previously acceptable implementation decisions may become outdated.

Someone needs to monitor these changes, review security reports, maintain dependencies, and provide updates when problems are discovered.

But what happens when the original developer leaves? Who takes responsibility when a vulnerability is reported? Is another maintainer prepared to continue the work? Are security updates still being released?

A publicly accessible repository can remain online long after meaningful development has stopped.

This introduces an important distinction: available source code is not necessarily maintained software.

When evaluating a project, it is worth looking at its release history, maintenance activity, security advisories, contributor structure, and documented continuity arrangements.

A project maintained by a small team is not automatically unreliable. Many successful projects have relatively small development teams. What matters is whether the project has the resources, processes, and commitment needed to respond to problems over time.

The same principle applies to proprietary software. A company can also discontinue a product, stop providing security updates, or reduce its maintenance resources.

The development model does not eliminate the need for ongoing responsibility.

The advantages of open source go beyond transparency

It would be unfair to discuss the limitations of open-source software without considering what makes the model valuable in the first place.

Publicly available code offers several practical advantages, particularly when the project is actively maintained and supported by people with relevant expertise.

Independent examination is one of the most important. Researchers are not limited to reviewing a developer’s explanation of its security architecture. They can investigate the available implementation, identify potential weaknesses, and publish their findings.

Community participation can strengthen development. Experienced contributors may identify problems, improve existing implementations, review changes, and help maintain software over time. A healthy project can benefit from a wider range of technical perspectives than its original development team alone.

Transparency can support accountability. Public repositories allow people to follow changes, examine development decisions, and question how particular features are implemented. This does not guarantee responsible behaviour, but it makes certain forms of independent scrutiny possible.

Flexibility can also be valuable. Depending on its licence, open-source software may allow users and organizations to modify, adapt, and redistribute the software under specified conditions. This can be particularly useful for organizations with specific technical requirements.

Cost is sometimes presented as another major advantage. Open-source software may be available without a licence fee, but that does not mean operating it is free. Hosting, maintenance, support, customization, security reviews, and ongoing development can all involve substantial costs.

The important point is that open source offers opportunities that can be valuable when supported by responsible development and adequate resources.

But those benefits should not be confused with automatic security or privacy guarantees.

Two Messaging Apps, Two Different Approaches to Privacy

I would also want to take instance of two messengers.

There is an interesting difference between the way messaging applications approach privacy, and it is not always visible when someone opens an app, sends a message, or starts an encrypted call.

Most users experience the same basic things: a contact list, a chat window, notifications, voice messages, and the reassurance that their conversations are protected. But behind that familiar interface, the decisions that shape how an application handles identity, communication, data, and security can be remarkably different.

Signal and xPal offer an interesting example of this. Both are designed around private communication and end-to-end encryption, yet they approach the underlying architecture from different directions.

Signal makes its software publicly available for inspection, while xPal uses a proprietary development model.

Signal uses phone-number-based registration alongside usernames and phone-number privacy controls, whereas xPal has built its account system around a nine-digit xID that does not require a phone number or email address.

These are not simply differences in branding or user experience. They reflect different decisions about what information a messaging platform needs, how its software can be examined, and what forms of privacy control it makes available.

Looking at Signal and xPal together allows us to examine a better privacy outcome.

The first difference appears before the first message

A messaging application begins collecting and processing information long before someone sends their first message. Account registration is one of the earliest architectural decisions, and it can determine which identifiers become part of a user’s relationship with the platform.

Signal requires a phone number to register an account. Over time, it has introduced additional privacy controls that allow users to limit who can find them through that number and use a Signal username to connect with others without necessarily sharing their phone number.

This is an important distinction: usernames provide another way to establish contact, but they do not eliminate the phone-number requirement during registration.

xPal approaches account identity differently. Instead of registering through a mobile number, users receive a nine-digit xID, which serves as their identifier within the platform.

The registration process does not require a phone number, email address, or SIM card, and users can communicate by exchanging their xIDs.

Neither approach exists without practical considerations. Phone-number registration is familiar and can make it easier to connect with people who already have one another’s numbers.

An independent identifier creates a different experience, where users decide who receives their xID rather than relying on a conventional telephone number as the starting point.

What matters here is not which identifier sounds more private, but what information each system requires and how that information is used. A username, a phone number, and a numerical account ID are not equivalent from a privacy perspective, and understanding their differences is more useful than simply describing an application as anonymous or private.

Open source and proprietary software are two different ways

The open-source distinction is probably the most visible difference between these platforms, but it deserves more careful consideration than it usually receives.

Signal makes its client applications, server software, and cryptographic libraries publicly available through its official GitHub repositories.

xPal takes a different approach. Its application is proprietary, meaning its complete source code is not publicly available for anyone to inspect.

Users cannot independently examine the entire application in the same way they can explore Signal’s public repositories.

Instead, xPal provides technical information about its architecture and points to external security assessments and cryptographic validation as part of its approach to demonstrating security.

These are different ways of making a case for confidence. One provides broader access to the underlying code; the other relies on published technical information and assessments conducted within defined scopes. Neither should be treated as a complete answer to the question of whether an application is secure.

I find this distinction particularly important because open source is sometimes discussed as though making code public automatically makes a product private. It does not.

Equally, a proprietary application cannot be judged solely by the fact that its source code is not public; its architecture, implementation evidence, external assessments, and actual data practices still deserve examination.

Also, both chat applications describe their communication systems as end-to-end encrypted, meaning messages are encrypted on the sender’s device and are intended to be decrypted on the recipient’s device. This is a fundamental protection because the service responsible for delivering a message should not need access to its readable contents.

Signal’s architecture is built around the Signal Protocol, which includes mechanisms such as the Double Ratchet algorithm and protocols for establishing shared encryption keys. The Double Ratchet continually derives new message keys as communication progresses, helping provide forward secrecy and protection against certain forms of key compromise.

xPal also documents the use of end-to-end encryption and describes several elements of its cryptographic architecture, including the Double Ratchet algorithm, PreKeys, a triple Elliptic Curve Diffie-Hellman handshake, Curve25519, AES-256, and HMAC-SHA256.

The presence of familiar cryptographic algorithms in both technical descriptions is worth noting, but it should not lead us to assume that the two implementations are identical. Cryptographic security depends on much more than the names of algorithms. Their implementation, key management, authentication, and integration into the wider application all matter.

There is also a difference in how independently the implementations can be examined. Signal’s public repositories allow researchers to inspect its available code and follow changes. With xPal, that level of public source-code inspection is not available, so other forms of technical evidence become particularly relevant.

For the xPal encrypted messaging app, these include its reported NIST Cryptographic Algorithm Validation Program results and external security assessments. It is important to be precise about what those results establish: NIST CAVP validates specified cryptographic algorithm implementations against applicable testing requirements; it does not certify an entire messaging application or independently establish every part of its privacy architecture. Similarly, an external security assessment should be understood through the particular version, components, and criteria covered by its report.

These distinctions matter because encryption is not a single feature that can be examined in isolation. It is part of a much larger system involving account security, device storage, message delivery, and the way information moves between users.

Another interesting difference appears when we move beyond the encryption of messages and look at what users can control after sending them.

Signal provides disappearing messages, view-once media, screen lock, and options for managing message history. It also offers ways to transfer or back up conversations, including its optional Secure Backups feature, which is designed around end-to-end encryption and a recovery key.

xPal has developed a different collection of controls around media, access, and conversation history. Its Photo and Video Sanitizer is designed to remove metadata from supported files before transmission, addressing information that may otherwise remain embedded in photographs and videos. Flicker mode provides disappearing messages, while users can also restrict recipients from downloading shared media.

Other xPal encrypted messaging app features address situations that are not directly related to message encryption. Remote Wipeout is designed to remove application data from a lost device once it reconnects to the internet.

Total Wipeout provides a reverse-PIN mechanism for deleting data, while Decoy Mode opens a separate environment containing dummy information.

Terminate allows users to remove a conversation and associated contact information from both participants’ devices, according to the company’s documentation.

These features address different situations, and it would be misleading to group them as though they all provide the same protection.

Media sanitization deals with information embedded in files. Disappearing messages manage how long messages remain visible. Remote deletion addresses device-loss scenarios, while decoy access is designed for situations involving unwanted access to an application.

There are practical limitations to consider, too. A disappearing message cannot guarantee that its recipient has not photographed the screen with another device. A remote wipe depends on the device eventually reconnecting to the internet. A feature that removes conversation history from participating devices cannot necessarily erase copies that someone has independently created elsewhere, like on anotherphone.

This is not a criticism of either platform. It is simply how digital privacy works: a feature can reduce a particular risk without eliminating every possible way information might be copied, retained, or exposed.

When I look at the differences between Signal and the xPal encrypted messaging app, what stands out is not that one has an open-source model and the other does not. It is that their architectures make different choices about identity, transparency, data handling, and the controls available to users.

These preferences do not have to produce one universal winner. Privacy is not a single measurement, and the strongest choice for one person’s circumstances may not be the same for someone with different communication habits or security concerns.

Editorial note: This is an opinion-led research piece, not a claim that open-source software is inherently insecure. The statistics describe the particular projects and vulnerabilities examined in that study; they should not be interpreted as measurements of every open-source application.