Software supply chain security has spent the last several years focused on source code, third-party packages, vulnerable libraries, and malicious dependencies. That focus made sense. Incidents like Log4Shell, dependency confusion, typosquatting, and compromised open-source packages made it clear that organizations needed better visibility into what their applications were built from.
That visibility still matters. SBOMs, dependency scanning, signed artifacts, vulnerability intelligence, and secure development frameworks are now part of the baseline conversation for software risk. The problem is that attackers are also moving past the obvious target. The next major software supply chain failure may not begin with a vulnerable function, a poisoned library, or a malicious commit. It may begin with everything around the code.
Modern software is no longer just written, reviewed, built, and shipped by people. It is assembled through CI/CD pipelines, package registries, GitHub Actions, build runners, signing keys, service accounts, AI coding assistants, secrets managers, release tokens, container builders, deployment automation, vendor portals, and third-party SaaS integrations. Every one of those pieces can influence what eventually runs in production. Every one of them can become a trust boundary.
That is the part many organizations still underestimate. A clean code review does not prove that the build process was clean. A dependency scan does not prove that the package came from the expected workflow. An SBOM does not prove that runtime behavior matches what was declared at build time. A vendor security questionnaire does not prove that release automation cannot be bypassed. Supply chain risk has moved into the operational machinery that turns source code into deployed software.
That shift changes the problem. The question is no longer just “what code are we using?” It is also “who or what was allowed to build it, sign it, publish it, modify it, and deploy it?”
The Supply Chain Is the System That Produces the Software
Many organizations still treat the software supply chain as a dependency inventory problem. They want to know which packages are present, which versions are vulnerable, and which vendors are connected to the product. That is a necessary starting point, but it is incomplete.
A modern release path can include dozens of non-code decisions that materially affect risk. A workflow file can define what runs during a build. A package registry token can authorize a release. A GitHub Actions trigger can decide whether untrusted pull request input reaches a privileged job. A build runner can hold environment variables, cloud credentials, signing material, or deployment permissions. A release artifact can be produced outside the expected process and still appear legitimate to downstream consumers.
From an attacker’s perspective, compromising the codebase is no longer the only path. It may not even be the easiest path. Stealing a publishing token can be more useful than landing a malicious pull request. Abusing a CI/CD workflow can be quieter than modifying application logic. Targeting a maintainer account can provide access that security tooling treats as normal. Manipulating the build process can place malicious behavior downstream without leaving obvious source-level evidence.
This is why supply chain security has to expand past repository scanning. The repository is only one layer. The release pipeline, identity model, artifact store, and deployment path are also part of the product.
The Nx Incident Showed the Risk Around Release Automation
The 2025 Nx supply chain attack is a clear example of this shift. The issue was not simply that a malicious package appeared in npm. The more important lesson was how the release path became the attack path.
Malicious versions of several Nx packages were published to npm after attackers exploited a GitHub Actions injection vulnerability and stole an npm publishing token. The packages were live for several hours and scanned user systems for sensitive data, including developer credentials and tokens. The payload also attempted to use local AI CLI tools, including Claude and Gemini, for reconnaissance and data exfiltration.
That incident matters because it ties several supply chain trends together at once. The attacker did not need a conventional application vulnerability in a production system. They targeted automation, publishing authority, developer workstations, secrets, and AI-assisted tooling. The trust placed in a widely used package became the delivery mechanism.
Nx later stated that the malicious packages lacked npm provenance signing, which helped identify that they did not come from the expected CI pipeline. That detail is important. Provenance did not prevent installation by itself, but it gave defenders a signal that the package did not match the normal release path. In a mature supply chain program, that signal should become enforceable policy rather than post-incident context.
This is where many organizations are still behind. They may scan dependencies after installation, but they do not always block artifacts that lack expected provenance. They may require MFA for maintainers, but still rely on long-lived publish tokens. They may review source changes, but leave workflow files, release triggers, and build permissions under weaker control.
The result is a supply chain model that trusts the final package more than it verifies the process that produced it.
Provenance Is Becoming More Important Than Package Name
For years, software trust has often been based on names and locations. Developers pull a package from npm, PyPI, Maven Central, GitHub, Docker Hub, or a vendor portal and assume that the package is what it claims to be. That model is fragile. Package names can be spoofed. Maintainer accounts can be compromised. Tokens can leak. Build jobs can be manipulated. Registries can host packages that are technically valid but operationally suspicious.
Provenance changes the question. Instead of asking whether a package came from a known place, defenders can ask whether it was built by the expected workflow, from the expected repository, at the expected commit, under the expected identity.
That distinction is becoming central to software supply chain security. A package name tells you what something claims to be. Provenance tells you how it came into existence. The second answer is much harder for an attacker to fake if the organization enforces it correctly.
This is why trusted publishing, artifact attestations, Sigstore-style signing, and SLSA-aligned build controls are becoming more important. They help move the supply chain from implicit trust to verifiable trust. A signed artifact with build provenance gives security teams a way to connect a release to the process that created it. A short-lived OIDC publishing flow reduces the value of stolen long-lived tokens. A dedicated build environment reduces the risk of local developer machines becoming the release authority.
None of this removes the need for code review or dependency scanning. It adds a missing control layer. Code can be safe and the release process can still be compromised. The inverse is also true: a package can look normal at the registry level and still fail provenance checks.
The organizations that treat provenance as optional metadata will have a harder time detecting this type of attack. The organizations that treat provenance as a deployment requirement will have a stronger control point before malicious artifacts reach production.
The Non-Human Identity Problem Is Growing
The next supply chain problem may also be an identity problem.
Software delivery is full of non-human identities. CI jobs authenticate to cloud providers. Build runners access artifact repositories. Deployment bots modify infrastructure. Package publishing workflows request tokens. Scanners read source code. Service accounts push container images. AI tools may access repositories, issue trackers, local files, terminal sessions, and internal documentation.
These identities often have more reach than individual users. They may run across multiple projects. They may be exempt from normal MFA requirements. They may hold long-lived credentials. They may be poorly documented. They may lack clear ownership. In many environments, these accounts are treated as plumbing rather than privileged access.
Attackers see the opposite. A non-human identity inside a build or release process is a high-value target. It can provide persistence, data access, publishing authority, cloud access, or deployment control. Compromising that identity can be more useful than compromising a single developer account.
This is especially dangerous in CI/CD environments. A pipeline is usually trusted to run code, access secrets, fetch dependencies, build artifacts, sign releases, and deploy changes. If an attacker can influence the pipeline, they can often cross boundaries that would be blocked in a normal user session.
The control model has to change. Release automation should not depend on broad, long-lived secrets stored in build systems. Workflows should use short-lived, scoped credentials where possible. Publishing should be bound to specific workflows and protected environments. Runners should be isolated by sensitivity. Secrets should not be exposed to untrusted pull request contexts. Build jobs should be treated like privileged production systems, not disposable developer conveniences.
The supply chain is now an identity graph. Organizations that cannot map that graph cannot reliably defend it.
AI Adds Another Supply Chain Layer
AI is adding a new layer to the software supply chain, and it is not limited to generated code.
Security teams are already paying attention to insecure code generated by AI assistants. That matters, but it is only part of the risk. AI tools are also being connected to repositories, terminals, ticketing systems, internal documentation, cloud environments, package managers, and build workflows. In some cases, AI agents can read files, write code, run commands, call APIs, open pull requests, summarize logs, modify configuration, or assist with releases.
That means AI tooling can become part of the development and delivery chain. If it has access, it has to be governed. If it can act, its actions have to be logged. If it can read secrets, the exposure has to be treated as real. If it can execute commands, the execution path has to be constrained.
The Nx incident showed one version of this problem from the attacker side: malware attempted to use local AI CLI tools for reconnaissance and exfiltration. That is a warning sign. AI developer tools are attractive to attackers because they may already have broad local context and user trust. They may know where projects are stored, how repositories are structured, which files look sensitive, and how to automate discovery across a workstation.
For defenders, this creates a hard policy question. Is an AI coding assistant just a developer productivity tool, or is it a supply chain participant? If it can influence code, configuration, tests, dependencies, release notes, infrastructure, or deployment logic, the answer is clear. It belongs in the supply chain model.
That does not mean organizations should ban AI development tools by default. It means they need controls that match the access level. AI tools should be restricted from secrets. Generated changes should go through the same review path as human-written changes. Agent actions should be logged. Tool permissions should be scoped. Local developer environments should not become uncontrolled bridges between repositories, cloud credentials, and AI execution.
The security concern is not that AI writes code. The concern is that AI tools are being connected to privileged development contexts faster than many organizations can inventory or govern them.
SBOMs Are Necessary, But They Are Not the Whole Answer
SBOM adoption has improved software transparency by forcing organizations to document the components inside their applications. That is valuable. It gives teams a way to answer exposure questions faster when a dependency vulnerability is disclosed. It also helps with vendor risk, procurement, compliance, and incident response.
Still, an SBOM is not a complete supply chain control by itself. It is an inventory artifact. It does not automatically prove that the build was trustworthy, that the published artifact matches source, that the runtime environment loaded only declared components, or that a package was produced by the expected workflow.
This gap matters during real incidents. A static SBOM can tell an organization what was expected to be present at a point in time. It may not reveal what actually executed in memory, what a malicious post-install script did during package installation, what a compromised build runner injected, or whether a release artifact was created outside the approved pipeline.
SBOMs should be paired with provenance, artifact signing, runtime visibility, and policy enforcement. The goal is not just to know what components exist. The goal is to know whether the software that reached production was built, signed, and deployed through a trusted path.
That is a higher bar. It also fits the direction of modern software risk. Static inventory helps answer “what is inside this application?” Provenance helps answer “can we trust how this application was produced?” Runtime validation helps answer “is the application behaving like the inventory said it would?”
All three questions matter.
Vendor Risk Has to Move Past Questionnaires
The same issue applies to third-party software vendors. Many organizations still evaluate software suppliers through questionnaires, SOC 2 reports, penetration test summaries, vulnerability disclosure policies, and security addendums. Those documents have value, but they rarely show the full release path.
A vendor can have a secure coding policy and still use weak release controls. A vendor can provide an SBOM and still lack enforceable artifact provenance. A vendor can require MFA for employees and still rely on overprivileged service accounts. A vendor can pass an audit and still have build runners with excessive network access, exposed secrets, or unreviewed workflow changes.
Procurement and security teams need to ask more operational questions. How are release artifacts signed? Are builds reproducible or at least traceable? Are package publishing tokens long-lived or replaced with trusted publishing? Are workflow changes reviewed as security-sensitive changes? Are build runners isolated? Are deployment credentials short-lived? Can the vendor prove which commit, workflow, and environment produced a given release? Can customers verify that proof?
These questions matter more than a generic statement that secure development practices are followed. A mature supplier should be able to explain how code becomes software and how that process is protected from tampering.
This is where supply chain security becomes a shared accountability problem. Buyers need stronger evidence. Vendors need stronger release controls. Security teams need to stop treating the vendor’s final artifact as the beginning of the risk conversation. The artifact is the end of a process. That process needs assurance.
What Defenders Should Prioritize Next
The next phase of software supply chain defense should focus on the systems that produce, publish, and deploy software.
Organizations should start by identifying their critical build and release paths. That means mapping repositories, CI/CD workflows, build runners, package registries, artifact stores, signing keys, service accounts, cloud roles, deployment jobs, and third-party integrations. This should include internal software and vendor-managed software that has privileged access to the environment.
Next, teams should reduce reliance on long-lived credentials. Package publishing, cloud access, and deployment automation should move to short-lived identity flows where possible. OIDC-based trusted publishing is a strong example of this pattern. If a token cannot be removed, it should be scoped narrowly, rotated regularly, monitored closely, and kept out of workflows that handle untrusted input.
Build provenance should become a policy control. Artifacts should be signed. Provenance should be generated by the build system. Production deployment should prefer, and eventually require, artifacts that can prove where and how they were built. This is the point where supply chain security becomes enforceable instead of advisory.
Workflow files should be treated as sensitive code. A change to a CI/CD pipeline can be as dangerous as a change to authentication logic. Pull request triggers, external contributor permissions, environment variable access, and secret exposure rules need review from people who understand both engineering and security impact.
Developer workstations also need more attention. Many supply chain attacks target the developer first, then move into repositories, secrets, package publishing, and cloud environments. Endpoint controls, secret scanning, local credential hygiene, and restrictions on package install scripts can reduce this risk. Development systems should not hold broad, reusable credentials that can turn one malicious package install into an organization-wide incident.
AI development tools should be added to the access review process. Security teams need to know which tools are in use, what data they can read, what commands they can run, and whether their actions are logged. AI-generated or AI-assisted changes should follow the same review, testing, and approval path as any other change.
SBOMs should continue to mature, but they should not be treated as a finish line. The stronger model is SBOM plus provenance plus signing plus runtime visibility plus deployment policy. That gives organizations a better chance of detecting mismatch between what was declared, what was built, what was shipped, and what actually ran.
The Next Problem Is Trust Without Verification
The software supply chain problem is no longer limited to unknown code. It is trust without verification across the systems that produce software.
A package can have the right name and still be malicious. A release can come from the right maintainer account and still bypass the expected pipeline. A build can pass tests and still leak secrets. A vendor can provide documentation and still lack defensible artifact controls. An AI tool can improve productivity and still create a new path into sensitive development context.
That is the next supply chain problem. It is not just the code organizations import. It is the authority granted to everything around that code.
Security teams need to treat the software factory as production infrastructure. CI/CD systems, package publishers, build runners, signing services, AI developer tools, and service accounts are no longer background components. They are part of the attack surface. They decide what becomes trusted software.
The organizations that understand this will move from dependency visibility to process assurance. They will ask for proof, not promises. They will verify artifacts, not just scan packages. They will govern automation, not just developers. They will treat the release path as a security boundary.
The next software supply chain problem may not be code. It may be the system that everyone already trusts to deliver it.
How Can Netizen Help?
Founded in 2013, Netizen is an award-winning technology firm that develops and leverages cutting-edge solutions to create a more secure, integrated, and automated digital environment for government, defense, and commercial clients worldwide. Our innovative solutions transform complex cybersecurity and technology challenges into strategic advantages by delivering mission-critical capabilities that safeguard and optimize clients’ digital infrastructure. One example of this is our popular “CISO-as-a-Service” offering that enables organizations of any size to access executive level cybersecurity expertise at a fraction of the cost of hiring internally.
Netizen also operates a state-of-the-art 24x7x365 Security Operations Center (SOC) that delivers comprehensive cybersecurity monitoring solutions for defense, government, and commercial clients. Our service portfolio includes cybersecurity assessments and advisory, hosted SIEM and EDR/XDR solutions, software assurance, penetration testing, cybersecurity engineering, and compliance audit support. We specialize in serving organizations that operate within some of the world’s most highly sensitive and tightly regulated environments where unwavering security, strict compliance, technical excellence, and operational maturity are non-negotiable requirements. Our proven track record in these domains positions us as the premier trusted partner for organizations where technology reliability and security cannot be compromised.
Netizen holds ISO 27001, ISO 9001, ISO 20000-1, and CMMI Level III SVC registrations demonstrating the maturity of our operations. We are a proud Service-Disabled Veteran-Owned Small Business (SDVOSB) certified by U.S. Small Business Administration (SBA) that has been named multiple times to the Inc. 5000 and Vet 100 lists of the most successful and fastest-growing private companies in the nation. Netizen has also been named a national “Best Workplace” by Inc. Magazine, a multiple awardee of the U.S. Department of Labor HIRE Vets Platinum Medallion for veteran hiring and retention, the Lehigh Valley Business of the Year and Veteran-Owned Business of the Year, and the recipient of dozens of other awards and accolades for innovation, community support, working environment, and growth.
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