Open Source Security Incidents Aren't Going Away

Companies and organizations need to recognize the importance of investing in engineers who possess both the soft and hard skills required to secure open source software effectively.

Michael Lieberman, Co-Founder & Chief Technology Officer, Kusari

November 11, 2024

6 Min Read
The words OPEN SOURCE on a digital background
Source: Yury Zap via Alamy Stock Photo

COMMENTARY

Open source security incidents aren't going away. The reliance on open source software (OSS) increases year-over-year, with more than 95% of all software, including open source, in some capacity. From operating systems to critical libraries to Web applications and more, open source software (OSS) plays a pivotal role in the current technology landscape. However, this widespread reliance introduces significant security risks. As the use of OSS continues to evolve, so does the importance of securing it. This responsibility falls not on individual hobbyist developers, but on the companies and organizations that have the resources to dedicate engineers specifically to open source security. These organizations are the ones that benefit the most from open source and should be the ones who contribute the most back.  

Essential Skills for Open Source Security Developers

Securing open source is similar to securing closed source, but many of the skills required are of higher importance for open source, due to various factors. Open source is public and tends to have broader adoption than much closed source software. A closed source tool with a security vulnerability used by a handful of customers is going to have a very different impact than something like OpenSSH having a vulnerability, given its use on millions of servers worldwide. 

I hope this doesn't come as a surprise, but the most important open source skills to have are soft skills. Most software development time is spent doing things other than actually writing code. Here are a few key skills:  

  1. Great Communication

  • Public collaboration: Open source projects are inherently collaborative and involve contributors from around the globe. Effective communication ensures that security practices are understood and implemented correctly. 

  • Preventing miscommunication: Many security bugs arise from misunderstandings. Clear documentation and open dialogues can prevent these issues from occurring. 

  • Proactive approach: Keeping security at the forefront of daily tasks helps in early detection of potential vulnerabilities. 

  • Continuous vigilance: A security-first mindset encourages constant evaluation of code for potential risks. 

  • Responsibility: Treating open source projects with the same seriousness as closed source commercial projects ensures higher security standards. 

  • Accountability: Developers who feel a sense of ownership are more likely to produce secure and reliable code. 

Just because soft skills are more important than hard skills for software development doesn't mean those hard skills are irrelevant. They are still important, and a few of them in particular are of focused importance for open source security. The open source community gets the benefit of a project being public, enabling the community to come together to secure the project with experts in different areas providing their expertise. However, with open source being public, it also exposes projects to malicious actors, like we saw in the XZ compromise, where a bad actor maintainer contributed innocuous-looking, but ultimately malicious, code. This is why software engineers focused on open source security need to be vigilant and experienced to know what to look for when they get contributions from anonymous developers. Here are some of the skills that are important: 

  1. Security Engineering and Threat Modeling 

  • Understanding attack vectors: Knowledge of how vulnerabilities are exploited is crucial. 

  • Techniques like STRIDE: Familiarity with threat modeling methodologies helps in identifying and mitigating risks. 

  • Common vulnerabilities: Awareness of issues like SQL injection, cross-site scripting (XSS), and buffer overflows is essential. 

  • Language-specific vulnerabilities: Each programming language has its own set of security concerns. This is especially important for languages and ecosystems that don't have built-in memory safety mechanisms. 

  • Ecosystem proficiency: Knowledge of the packaging ecosystem like PyPI, npm, etc., and how software is developed in that ecosystem is important to understand external risks to the project like upstream dependencies. You can write perfectly safe code and include a vulnerable or malicious dependency and ship insecure software. Knowing when to include a dependency and when it's better to write the functionality yourself is very important as well. 

  • Build pipelines: Incorporating security checks into continuous integration and deployment processes ensures ongoing security. Open source developers wear multiple hats and need to understand and secure the continuous integration flow. The artificial intelligence (AI) analog would be the training pipeline. 

  • Contextual awareness: Understanding how software will be used by consumers helps in identifying potential security flaws. 

  • Automated testing: Implementing tools that automatically scan for vulnerabilities can catch issues early. 

  • Comprehensive test coverage: Ensuring that all parts of the code are tested reduces the risk of overlooked vulnerabilities. 

As the reliance on open source software continues to grow, so does the necessity for open source developers focused on security. This need is becoming even more critical with the rise of open source AI projects. Open source AI introduces new layers of complexity and opacity due to massive datasets and the probabilistic nature of trained models. The sheer volume of data and the intricacies of machine learning algorithms make it challenging to identify vulnerabilities and predict how models might behave in unforeseen circumstances. 

The "black box" aspect of AI models means that even the developers may not fully understand how inputs are being processed to produce outputs. This opacity can be exploited, leading to security breaches such as data poisoning, adversarial attacks, and unintended bias. Therefore, securing open source AI requires specialized skills and a deep understanding of both AI technologies and security principles. 

Companies and organizations must recognize the importance of investing in engineers who possess both the soft and hard skills required to secure open source software effectively, especially in the rapidly evolving field of AI. By fostering these skills, we can enhance the security of open source projects, benefiting individual organizations and the global community that relies on them. 

About the Author

Michael Lieberman

Co-Founder & Chief Technology Officer, Kusari

Michael Lieberman is co-founder and chief technology officer (CTO) of Kusari, where he helps build transparency and security in the software supply chain. He has extensive engineering and architecture expertise with an emphasis on cloud-native technologies and security and privacy use cases. Prior to Kusari, he held engineering leadership positions with Citi, Mitsubishi UFJ Financial Group (MUFG), and Bridgewater Associates. Michael is an active member of the open source community, co-creating the GUAC and FRSCA projects and co-leading the CNCF’s Secure Software Factory Reference Architecture white paper. He is also co-chair of the Cloud Native Computing Foundation Financial Services User Group and an OpenSSF TAC and SLSA steering committee member. 

Keep up with the latest cybersecurity threats, newly discovered vulnerabilities, data breach information, and emerging trends. Delivered daily or weekly right to your email inbox.

You May Also Like


More Insights