Interconnected web of software packages with vulnerabilities spreading through the network, protected by AI.

Decoding Software's Hidden Webs: How Vulnerabilities Spread and What We Can Do About It

Nico Varela in Tech & Innovation December 2025 • 5 min read.

"A new study uncovers the systemic risks lurking in software dependency networks and reveals surprising insights into effective protection strategies."

In today's digital world, we rely on software for nearly everything. But what happens when that software has hidden weaknesses? Imagine a single faulty update bringing major operations to a standstill – it sounds like something from a disaster movie, yet that is what happened in 2024. A faulty update to the software Crowdstrike, a security software, created worldwide panic and disruptions, paralyzing domestic and international air traffic, disrupting operations at banks, hospitals, and hotel chains. This incident shined a light on systemic risk: the danger that a problem in one part of a system can spread and cause widespread chaos.

Now, researchers are digging deep into these risks, and a recent study sheds light on how vulnerabilities spread through interconnected software components. This isn't just a technical issue; it has real economic consequences. The Heartbleed bug, a vulnerability in the OpenSSL authentication library used by millions of websites, compromised sensitive data and disrupted operations, costing at least $500 million in damages. According to the risk management company Parametrix, the disruption caused by Crowdstrike cost Fortune 500 companies $5.4 billion.

The interconnected nature of modern software is a double-edged sword. On one hand, reusing existing code can save time and resources. On the other hand, it creates complex webs of dependencies, where a vulnerability in one component can ripple outwards, affecting countless other programs. That’s why understanding these 'vulnerability webs' is so critical to protecting our digital infrastructure. So, how can we protect our software and minimize these risks? Recent research offers new strategies.

The Economics of Code Reuse: Why Dependencies Matter

Interconnected web of software packages with vulnerabilities spreading through the network, protected by AI.

Modern software development is a collaborative ecosystem. Developers frequently reuse existing code to reduce development and maintenance costs. The reuse of code, however, introduces vulnerabilities in the form of undetected bugs in direct and indirect dependencies, as demonstrated by Crowdstrike and HeartBleed bugs. While reusing code boosts efficiency, it also creates a network of dependencies. When developers incorporate code from other packages rather than creating their own, they might unknowingly introduce vulnerabilities. It's like building a house with materials from different sources – if one source has a defect, the whole structure could be weakened.

Researchers have modeled this issue as a network formation game, where developers decide whether to create dependencies based on perceived costs and benefits. The analysis of open-source software projects reveals that maintainer's decision to allow a dependency exerts a negative externality on other maintainers, meaning that one developer's decision to rely on external code can create risks for others. This negative effect discourages the formation of dependencies and partially contributes to the sparsity of the network. The cost of losses from software failures are huge, Krasner (2018) put the cost of losses from software failures at over $1 trillion, up from $59 billion in 2002 estimated by the National Institute of Standards and Technology (2002).

The Dependency Dilemma: Reusing code saves time but creates potential security risks.
The Externality Effect: One developer's choice to use external code can impact the security of others.
Economic Impact: Software failures can result in trillions of dollars in losses, highlighting the importance of secure code.

This creates a situation where the benefits for individual developers (reduced cost, faster development) may not align with the overall health of the software ecosystem. Therefore, ensuring that such packages are free of vulnerabilities that can potentially affect a large number of other software packages is particularly important.

The Future of Secure Code

Understanding the dynamics within software networks is crucial to mitigating systemic risk. By recognizing the economic costs and the potential of new technologies, we can work towards a more secure and resilient digital world. This is not merely a technical challenge but a strategic imperative that requires ongoing attention and adaptation. Modern software development is about managing complex relationships and understanding the incentives that drive developers' decisions. By addressing the challenges of vulnerabilities and by harnessing the power of AI, we can secure the digital infrastructure that underlies our modern society.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: https://doi.org/10.48550/arXiv.2402.13375,

Title: Vulnerability Webs: Systemic Risk In Software Networks

Subject: econ.em

Authors: Cornelius Fritz, Co-Pierre Georg, Angelo Mele, Michael Schweinberger

Published: 20-02-2024

Everything You Need To Know

What is systemic risk in the context of software, and why is it a concern?

Systemic risk in software refers to the potential for a vulnerability in one part of a software system to spread and cause widespread disruption. This is a major concern because modern software relies on interconnected components, creating complex dependency webs. A single faulty update, as seen with the Crowdstrike incident, can lead to global chaos, impacting critical infrastructure like air traffic, banking, and healthcare. The Heartbleed bug also demonstrated the potential for widespread damage, leading to significant financial losses and data breaches. The economic impact of such failures can reach trillions of dollars, making systemic risk a critical issue for digital infrastructure and the global economy.

How does the reuse of code in software development introduce vulnerabilities?

The reuse of code, a common practice in modern software development, introduces vulnerabilities through dependencies. When developers incorporate code from external packages to save time and resources, they might unknowingly introduce undetected bugs. These dependencies create networks where a vulnerability in one component can affect many other programs. The dependency dilemma highlights this trade-off: while code reuse boosts efficiency, it increases the risk of vulnerabilities spreading throughout the system, as demonstrated by the Crowdstrike and HeartBleed bugs. This creates a situation where individual developers' benefits may not align with the overall security of the software ecosystem.

What is the 'externality effect' in software dependency networks, and how does it impact security?

The 'externality effect' describes the impact one developer's decision to use external code has on the security of other developers. In the network formation game, a maintainer's decision to allow a dependency can create risks for other maintainers. This negative externality discourages the formation of dependencies and partially contributes to the sparsity of the network. If a developer chooses to rely on an external package with vulnerabilities, they not only put their own software at risk but also potentially expose other software packages that depend on the same vulnerable component. This widespread impact underscores the importance of thoroughly vetting dependencies to ensure the overall health and security of the software ecosystem.

What are some real-world examples that demonstrate the economic impact of software vulnerabilities?

The economic impact of software vulnerabilities is significant, as demonstrated by several real-world examples. The Crowdstrike incident in 2024 caused widespread disruptions across various sectors, with Fortune 500 companies incurring $5.4 billion in damages. The Heartbleed bug, a vulnerability in the OpenSSL authentication library, resulted in at least $500 million in damages. These examples highlight the substantial financial losses that can arise from software failures. In addition, Krasner (2018) estimated that the cost of losses from software failures exceeds $1 trillion, showcasing the importance of secure coding practices and robust vulnerability management strategies to mitigate these economic risks.

How can new technologies, like AI-assisted coding, help improve software security and reduce systemic risk?

New technologies, such as AI-assisted coding, can revolutionize our approach to systemic risk by understanding the dynamics within software networks. These technologies can help detect vulnerabilities early in the development process. By analyzing code and dependencies, AI can identify potential weaknesses before they are introduced into production systems, reducing the likelihood of widespread failures. Furthermore, AI can help automate the process of patching vulnerabilities and mitigating risks, improving the overall security and resilience of software. Harnessing the power of AI is a strategic imperative to create a more secure digital infrastructure, enabling us to address the challenges of vulnerabilities and enhance the safety of the software that underlies modern society.