Open source is the foundation of modern software. Studies show that 96% of enterprise software applications include open source components, and 70–90% of every codebase consists of open source modules. Anaconda’s research illustrates that reality, too: 91% of IT workers report using open source software in their current workflow. That ubiquity brings transparency, rapid innovation, community collaboration, and access to cutting-edge tools that would cost a fortune to build from scratch.

It also creates widespread cybersecurity risk. A single vulnerability in a widely used open source package is a potential entry point into thousands of systems simultaneously—but most organizations lack the automated security solutions needed to manage open source risk at scale. In fact, less than one-third of organizations use automated security testing tools when evaluating open source components.

This article explains what open source software security is, why it matters, what risks organizations face, and what tools and best practices can help teams protect their software supply chains more effectively.

What is Open Source Security?

Open source security refers to the practices, tools, and policies organizations use to identify, manage, and mitigate security risks in open source software throughout the development lifecycle. It encompasses everything from tracking known vulnerabilities in third-party packages to enforcing policies around which software components are permitted in a production environment.

Unlike proprietary software, where a single vendor controls the codebase and is responsible for patches, open source software (OSS) is developed and maintained by distributed communities. That decentralized model is a strength in many respects: bugs get spotted quickly, improvements happen rapidly, and the source code is transparent by design. But it also means there’s no central authority to ensure every package is up to date, vulnerability-free, or built with enterprise security requirements in mind.

Open source security is ultimately about protecting your software supply chain. Every piece of open source code your team relies on is a dependency, and every dependency is a potential point of failure. Organizations that manage open source risk systematically are better positioned to catch vulnerabilities before they become breaches (and to respond faster when they do).

6 Open Source Security Risks and Challenges

Open source software introduces a distinct set of security challenges that differ meaningfully from those associated with proprietary software. Understanding these risks is the first step toward improving your supply chain security posture.

1. Supply chain attacks

A supply chain attack occurs when a threat actor compromises a widely used open source package or repository, causing organizations to unknowingly pull malicious code into their own systems. Two common techniques are typosquatting, where attackers publish packages with names nearly identical to popular libraries, and dependency confusion, where a malicious public package is substituted for a legitimate private one during the build process.

A well-known example is the March 2026 Axios compromise, in which attackers introduced a malicious dependency into two releases of axios, the most popular JavaScript HTTP client library. Axios sees over 100 million weekly downloads, meaning even a three-hour exposure window created significant downstream risk for thousands of organizations. Google’s Threat Intelligence Group noted that given the package’s reach, the full breadth of the incident remained unclear even after the malicious versions were removed.

2. Outdated software and unpatched vulnerabilities

Outdated open source software—packages running past their patch date or beyond vendor support—is among the most exploitable and avoidable sources of enterprise risk. Many organizations continue to run open source packages long after security patches have been released. This happens for a variety of reasons: teams are unaware a patch exists, updating a dependency risks breaking something else, or there simply is not bandwidth to keep everything current. The result is a growing backlog of known, exploitable vulnerabilities sitting inside production systems.

The 2017 Equifax breach illustrates how much damage an unpatched open source vulnerability can cause. Apache Struts (CVE-2017-5638), a critical remote code execution flaw in an open source Java web framework, was publicly disclosed and patched on the same day. But Equifax hadn’t applied the patch, and within three days, attackers were inside its network. The attackers went undetected for the next two months, stealing the personal data of over 147 million people. It was a preventable breach—one that reportedly cost Equifax $1.38 billion in settlements and security improvements.

3. Complex and transitive dependencies

Transitive dependencies are the indirect dependencies that get introduced when an open source package pulls in other packages of its own. They create chains of third-party code that can be difficult to track and even harder to audit.

That’s what happened with XZ Utils, a compression library bundled in virtually every major Linux distribution. In 2024, a Microsoft engineer discovered a malicious backdoor in XZ Utils that had gone undetected for nearly two years. The backdoor was introduced through the project’s GitHub repository by a threat actor who had spent years gaining the primary maintainer’s trust. The attack could have compromised nearly every server on the internet, and yet a standard vulnerability scan of direct dependencies never would have found it.

4. Limited security resources in some projects

Many widely used open source libraries are maintained by small volunteer teams or individual contributors who lack the resources for dedicated security testing or rapid vulnerability response. When a security issue is discovered, response time can vary significantly. In some cases, projects are abandoned entirely, leaving known vulnerabilities unpatched indefinitely.

Without dedicated tooling or processes, most tech professionals don’t feel fully confident managing OSS risks. In fact, an Anaconda survey of more than 2,400 practitioners found that only 18% of IT workers feel very confident in their ability to identify and remediate open source vulnerabilities.

5. Threat actors are targeting open source directly

Open source repositories are high-value targets for cybersecurity threat actors, since compromising a popular package is a force multiplier: one malicious commit can propagate to thousands of downstream systems simultaneously. That means the scale and trust that make open source valuable are the same traits that make it so attractive to attackers.

6. Shifting liability

Regulatory frameworks in the U.S. and EU are increasingly placing accountability for software security (and software integrity) on the organizations that ship it—including accountability for vulnerabilities in the open source components those products contain. Guidance from the U.S. Cybersecurity and Infrastructure Security Agency (CISA) and the EU Cyber Resilience Act (CRA) both reflect this shift. Organizations subject to CISA guidance or the EU CRA face direct regulatory exposure if open source components go unmanaged.

Best Practices for Open Source Security

Securing an open source software environment requires a layered approach and a commitment to ongoing automation, with security built into every stage of the development process. This approach requires a DevSecOps (development, security, and operations) mindset that integrates security practices and tools into every stage of the DevOps (development operations) pipeline. No single tool or policy is sufficient on its own.

These best practices address the most common sources of risk.

Package management

Using public repositories without any additional controls introduces unnecessary risk. Organizations should use private or mirrored repositories that apply security screening before making packages available to developers. Private repositories allow development teams to enforce policies centrally, ensuring that only approved packages with acceptable vulnerability profiles make it into the development environment.

Controlling which specific repositories packages are pulled from (and standardizing on common base versions across projects) also reduces exposure to dependency confusion attacks and makes it easier to apply security updates consistently.

Package sources

Teams should evaluate sources based on the security practices of their maintainers, the freshness of their vulnerability data, and the level of curation they apply.

Most vulnerability scanning tools rely on the NIST National Vulnerability Database as their primary source of common vulnerabilities and exposures (CVE) data. Since early 2024, NIST has been unable to keep pace with a surge in CVE submissions, which has led to a backlog of vulnerabilities without severity scores or descriptions. Anaconda manually curates CVE data for the packages in its ecosystem and provides the enrichment that the NVD increasingly cannot. That means teams can make informed decisions about the vulnerabilities in their environment, rather than working from incomplete or missing data.

Package versions

Security patches are frequently released in minor or patch-level version updates. Organizations that pin dependencies to older versions (or simply fail to update regularly) are leaving known vulnerabilities in place without a structured vulnerability management process.

When evaluating version upgrades, teams should assess the vendor’s support schedule, whether the update introduces breaking changes, the severity of the vulnerabilities addressed, and how the new version interacts with other dependencies in the environment.

Working with environments

Isolating project dependencies using environment management tools reduces the blast radius of any single vulnerability. Whether teams are working locally or deploying to cloud environments like AWS, isolated environments ensure that a compromised package in one project cannot directly affect others.

Tools like conda make it straightforward to create, share, and switch between project-specific environments, enabling teams to enforce separation without slowing down development workflows.

Dependency management

Teams should include only the packages a project genuinely requires, since every added dependency is another attack surface. Before adding a new dependency, developers should ask whether the functionality could be achieved using language built-ins, existing libraries, or a well-maintained API already in the environment.

Transitive dependencies deserve particular attention. A package that appears safe on its own may pull in a chain of secondary dependencies with significant security issues. Regular security audits of your dependency trees can complement automated scanning, and they may catch issues that other tools miss.

Types of Open Source Security Tools

A range of specialized tools exists to help organizations identify and address security vulnerabilities in their open source environments. These tools are typically integrated into the DevOps pipeline and can catch security issues early before code gets deployed.

Static Application Security Testing (SAST)

SAST tools analyze source code or compiled binaries without executing them, scanning for patterns associated with known vulnerabilities. These tools are typically integrated into the development pipeline and can catch security issues early in the software development lifecycle, before code gets deployed.

Dynamic Application Security Testing (DAST)

DAST tools test running apps by simulating external attacks against live endpoints and interfaces the way a real attacker would. They help identify vulnerabilities that only manifest at runtime, such as injection flaws or authentication weaknesses.

Software Composition Analysis (SCA)

SCA tools inventory the open source components used in an application, map them against databases of known vulnerabilities such as the National Vulnerability Database (NVD), and flag dependencies that demand remediation.

Container scanning tools

Container scanning tools inspect images for vulnerable operating system packages, application dependencies, and misconfigurations before those images are pushed to registries or deployed to production.

Security package managers

These tools extend standard dependency resolution with built-in vulnerability screening and policy enforcement. They can block the installation of packages that fail to meet defined security criteria before they enter a development environment.

Beyond individual tools, cross-industry initiatives like the Open Source Security Foundation (OpenSSF) have developed frameworks such as Scorecard, which automatically assesses the security practices of over one million open source projects to help teams evaluate whether dependencies are actively maintained and following sound security practices.

Anaconda’s Approach to Open Source Security

Anaconda has been part of the open source data science and AI community for more than a decade, and securing that ecosystem is central to its mission. With over 50 million users and 21 billion downloads, Anaconda understands what it takes to make open source software enterprise-ready.

Anaconda’s platform addresses the full spectrum of open source software security challenges through a combination of curated repositories, vulnerability intelligence, and AI governance tooling built specifically for AI and data science environments.

Secure, curated package repositories

Anaconda Core provides access to a curated repository of packages that have been vetted for security and stability, helping teams reduce their exposure to malicious or unmaintained packages. Anaconda extends that coverage to conda-forge packages through CVE association, giving teams visibility into vulnerabilities in conda-forge packages mirrored to their secure repository.

CVE curation and vulnerability intelligence

Vulnerability databases are only as useful as the data they contain. False positives waste engineering time, and false negatives leave risks unaddressed. Anaconda curates CVE data for the packages in its ecosystem, improving the accuracy of vulnerability intelligence so teams can prioritize remediation efforts on issues that actually matter.

For more information, see Anaconda’s guide on OSS security with Python.

AI Catalyst for advanced security and governance

Anaconda’s AI Catalyst extends that governed distribution approach to open source AI models. Rather than pulling models directly from unmoderated sources, teams get a catalog of models that have been vetted and validated by Anaconda. Internal policy controls ensure developers can use the latest organization-approved models, and a controlled inference stack helps reduce vulnerabilities and catch model-specific risks before they reach production. AI Catalyst helps teams accelerate deployment from months to days while maintaining enterprise security standards.

Environment management with conda

Anaconda makes it easy to create isolated, reproducible environments. By giving teams a consistent, controllable way to manage dependencies, Anaconda reduces the operational complexity that often leads to security debt.

Open-source tools will continue to be the engine of data science and AI innovation. But realizing its benefits without accepting unnecessary risk requires a deliberate, systematic approach to the security of open source at every layer of the software supply chain. Anaconda provides the platform, the tools, and the expertise to help organizations do exactly that.

Ready to see how Anaconda can help secure your open source environment? Request a demo or get started free today.