Why do open source packages and third-party code increase application security risk?

Open source and third-party code expand attack surface because teams no longer control every line of code that enters the build. That introduces vulnerable dependencies, malicious packages, and hidden exposures such as leaked secrets. In cloud-native and CI/CD environments, those risks scale quickly, so organisations need controls that identify what is present, what is trusted, and what must be remediated first.

Why Open Source and Third-Party Code Change the Risk Profile

Open source and third-party components change application security because they insert trust boundaries the development team does not fully control. The risk is not limited to vulnerable libraries. It also includes dependency confusion, compromised maintainer accounts, transitive packages, and code paths that arrive through build tooling rather than deliberate design. For application teams, that means security now depends on provenance, update hygiene, and visibility into what actually ships.

That matters most in modern delivery pipelines, where a package can be introduced once and propagated across many services, environments, and releases before anyone notices. Teams often assume that a popular package is effectively safe, but popularity does not remove the need to verify source, integrity, and maintenance state. For a broader control perspective, the NIST Cybersecurity Framework 2.0 is useful because it frames the problem as governance, risk, and supply-chain hygiene rather than a single code-scanning task. In practice, many teams discover dependency risk only after a build failure, a security advisory, or an unexpected package update has already entered production.

How Supply-Chain Risk Shows Up in Real Builds

Third-party code increases risk because it expands both the attack surface and the number of assumptions a team must trust. A package manager does not just fetch code; it also resolves versions, evaluates metadata, follows transitive dependencies, and often executes install-time logic. Each of those steps can create exposure if the package has been compromised, is no longer maintained, or is pinned too loosely for safe change control.

In practice, the most important failures are often not dramatic exploits but ordinary operational weak points. A developer may add a library to move faster, yet that library may bring in a vulnerable subdependency several layers deep. A build may pull the wrong package name from a public registry. A dependency may appear stable until a maintainer account, release process, or signing step is abused. Even when the code itself is legitimate, it can still leak secrets through logs, bundle unneeded functionality, or keep dormant code paths that no one tests.

Provenance matters because the team must know where code came from before it can decide whether to trust it.
Version control matters because broad version ranges can silently pull in risky changes.
Transitive dependency visibility matters because hidden packages often carry the actual vulnerability.
Build hygiene matters because secrets, tokens, and private endpoints can be exposed during install or test steps.

For teams that want a control-oriented view of these problems, NIST guidance helps connect software supply-chain concerns to broader security governance, but it does not replace application-level review of package behaviour. Where organisations rely on frameworks, they should treat dependency trust as a lifecycle issue, not a one-time approval. That also means scan results are only useful if they are tied to ownership, patch timing, and release decisions. This guidance breaks down when teams treat package inventory as a static list instead of a continuously changing part of the delivery system.

When “Open Source” Is Safe Enough and When It Is Not

Tighter dependency controls often increase delivery overhead, so organisations have to balance speed against the cost of verification. The practical question is not whether open source is good or bad, but whether the component is well governed, actively maintained, and used in a way that matches its trust level.

There is no universal consensus that openness itself reduces risk. In security operations, the useful distinction is between transparent code and trustworthy code. A widely used package with active maintenance and clear release history may be easier to assess than a closed component with no visibility. At the same time, a well-known package can still become risky if maintainers are compromised, dependencies are abandoned, or new functionality is pulled in without review. Security teams should be especially cautious when the same package is reused across many services, because one weak dependency can become a shared failure point.

The most overlooked edge case is that risk can come from the integration layer rather than the package content itself. Generated artefacts, install scripts, CI runners, and deployment credentials often sit around the code and inherit its trust. That is why dependency governance and secret handling need to be considered together, not separately. If a team cannot explain who can publish, update, approve, and remove a dependency, it does not yet have the level of control needed for high-confidence software delivery.

Risk and Threat Considerations

Open source and third-party code create supply-chain exposure because the organisation inherits trust in external maintainers, registries, and transitive packages. The risk is not only accidental vulnerability introduction. It also includes malicious package insertion, account compromise, and build-path abuse that can turn ordinary dependency resolution into a delivery vector.

Failure mechanism: Attackers and other abusers target the places where trust is easiest to inherit and hardest to inspect, such as package names, maintainer credentials, update channels, and install-time behaviour. A compromised dependency can bring in harmful code, while a legitimate dependency can still expose secrets, increase privileges, or expand the reachable attack surface through transitive pulls and automated builds.

Impact: The result can be code execution in the build pipeline, secret exposure, compromised production releases, or a latent vulnerability distributed across many applications at once. Because dependencies are reused, one failure can scale from a single repository to an organisation-wide trust problem.

Standards & Framework Alignment

This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.

MITRE ATT&CK address the attack and risk surface, while CIS Controls v8 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.

Framework	Control / Reference	Relevance
CIS Controls v8	2 — Inventory and Control of Software Assets	Third-party packages are software assets that must be inventoried and governed.
	7 — Continuous Vulnerability Management	Dependencies create ongoing vulnerability exposure that must be monitored and remediated.
Recommendation — Inventory all approved packages and remove untracked dependencies from builds. Continuously scan dependencies and prioritise remediation for exposed libraries.
NIST CSF 2.0	ID.SC-4 — Supply Chain Risk Management	Third-party code is a software supply-chain dependency that requires governed trust decisions.
	PR.DS-6 — Integrity Verification	Package integrity and provenance checks help detect tampered or altered code.
	GV.SC-8 — Supply Chain Risk Management	Managing software dependencies requires clear supply-chain governance and oversight.
Recommendation — Assess supplier and package trust before allowing dependencies into production. Verify package integrity and signing before build systems consume updates. Assign supply-chain ownership for dependency approval, review, and exception handling.
MITRE ATT&CK	T1195 — Supply Chain Compromise	Compromised third-party code is a recognised supply-chain attack path.
Recommendation — Hunt for compromised dependency insertion and malicious update activity in pipelines.

Practitioner Guidance

What to prioritise: Focus first on the dependencies that are both widely reused and easiest to auto-update, because those are the paths most likely to propagate risk quickly across services. High-churn packages and transitive dependencies deserve more attention than low-use libraries that rarely change.

What to verify: Confirm that each critical dependency has a known owner, a stable source, and an update policy that matches the application’s release cadence. If the team cannot trace provenance or explain why a package is present, treat that as a governance gap, not just a scan finding.

Common mistake: Teams often treat vulnerability scanning as complete control, but scanning only finds known issues after they already exist in the build. The stronger judgement is whether the organisation can prevent untrusted code from entering the pipeline in the first place and can remove it quickly when trust changes.

Practitioner takeaway: Dependency risk is really a trust-management problem, so the best control is not more code volume but better visibility into provenance, reuse, and approval ownership.