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How Open Source Can Benefit AI Development

Enterprises are increasingly reliant upon open source software. A full 95% of IT leaders say open source tools are key to their enterprise infrastructure. Simultaneously, we’ve witnessed a sharp increase in the adoption of artificial intelligence (AI) and machine learning (ML). Most IT divisions want to take advantage of AI in some form, and open source technologies will likely be vital to these efforts.

I recently met with Moses Guttmann, co-founder and CEO of ClearML, to understand the benefits of adopting open source software within the sphere of artificial intelligence. To Guttmann, open source has many benefits—the visibility it grants can equate to helpful feedback from the developer community, and transparency can inform new feature development and identify potential security gaps. There are also countless open source tools to help organizations develop and deploy ML models.

Below, we’ll consider the benefits and potential drawbacks of incorporating OSS in AI development and explore ways to optimize the use of AI within an organization.

Benefits of Using Open Source for AI

AI has evolved in leaps and bounds. What was pure sci-fi a few years ago has become a reality through ChatGPT and other AI-powered platforms. The capabilities of AI are awe-inspiring, but Guttmann believes it still requires fine-tuning to move from entertainment purposes into a valid business driver.

For example, custom ML models are difficult to construct from scratch, and generic APIs aren’t always that customized to the use case at hand to be valuable. Instead, Guttman foresees more and more organizations downloading open pre-trained models and retraining or customizing them to meet their specific needs.

For software providers, there are many benefits to adopting an open source strategy. The visibility it creates helps evolve a project with feedback from the community, said Guttmann. This, in turn, helps organizations build better, more stable products. For example, ClearML adopts plenty of OSS to power their user interface, backend and other components, in addition to providing a popular open source CI/CD framework for ML workflows. “We’re true believers in the power of community and like to work with open source and contribute back to these projects,” said Guttman.

Use Cases for Open Source in AI Development

Open source software is powering innovation in many ways. And when it comes to AI, there are numerous open source projects to help accelerate AI development. Such projects encompass pre-trained models, data-structuring tools, frameworks to train models and AI deployment pipelines. For example, many open source machine learning frameworks can help engineers build and train their models from scratch. These free-to-use tools include TensorFlow, Keras, PyTorch, H2O, XGBoost and others.

However, training models from scratch is time-intensive and complicated, said Guttmann. Instead, another option is to use pre-trained models accessible on GitHub or other repositories. Some popular examples are PaddleNLP and Natural Language Toolkit for natural language processing, OpenCV for machine vision and DeepFaceLab for deepfakes. There are also many open source Python packages that can structure and clean data for ML model training purposes.

Open source software can also be applied to streamline the ML DevOps pipeline itself. AI requires intense processing and is typically deployed to its own computing environments. Infrastructure management around running and training AI is a promising area where open source could assist, said Guttmann. “Automating this process with an abstraction layer to allow data science and ML engineers to access product-grade hardware is a must,” said Guttmann.

Potential Downsides of Open Source Usage

Yet, of course, there are some potential downsides to using open source software within the field of AI. Supply chain attacks are still a persistent threat, and numerous open source software risks can present themselves. These include bad actors compromising a legitimate package, name confusion attacks, unmaintained software and untracked dependencies. License restrictions could also potentially block the inclusion of OSS in certain projects.

Thankfully, the benefits of OSS appear to outweigh these concerns. Automated vulnerability scanning techniques can help detect known issues. It also helps that 89% of technology leaders see enterprise open source as more secure or as secure as proprietary software, according to a Red Hat report.

Tips For Getting the Most From AI

Open source is powering digital innovation on many fronts, including AI. But, simply looping in OSS isn’t the only aspect of fully leveraging AI—another will be the operationalization of ML management. The right automation infrastructure in place could enable the agility necessary to continuously retrain models. And since there are potential gaps in the CI/CD process, Guttmann recommended separating AI/ML from your normal CI/CD for security reasons.

Guttmann also believes that, in general, companies should be more transparent around ML models, including sharing details behind their creation and visibility regarding the datasets fed into them. Overlooking this could lead to ethical concerns. Furthermore, limiting the “hallucinations” generative AI produces is another huge gap that must be bridged, said Guttmann. This could be solved by simply allowing the system to respond with “I don’t know,” instead of confidently spouting nonsense.

In summary, open source could bring many benefits to bespoke AI/ML adoption. Many mature open source tools exist to enable engineers to create advanced AI and oversee the management and deployment of custom ML models. But the real test will be retaining this open creed by upholding visibility and transparency into the end creations.

March 16, 2023
Report Identifies Top 10 Open Source Software Risks

Endor Labs, a provider of a platform for managing open source software, published a report that classifies the top 10 open source software risks of 2023. The company published the list as part of an effort to better educate application development teams about issues that can lead to software supply chain compromises. That list includes:

Known Vulnerabilities: A version of a software component may contain vulnerable code that is accidentally introduced by its developers. When vulnerability details are publicly disclosed, there may not be a patch readily available.

Unmaintained Software: A software component may not be actively developed or maintained anymore, resulting in patches for functional and non-functional bugs not being provided in a timely manner—if they’re provided at all.

Name Confusion Attacks: Attackers may create components whose name resembles the names of legitimate open source or system components. This is also known as typosquatting. Bad actors might also attempt to mimic trustworthy authors (brandjacking) or play with common naming patterns in different languages or ecosystems (combosquatting).

Compromise of Legitimate Package: Attackers may compromise resources that are part of an existing, legitimate project or associated distribution infrastructure to inject malicious code into software components.

Outdated Software: A project may use an old, outdated version of a software component even though a newer, more secure version exists.

Untracked Dependencies: Developers may not be aware of a dependency on a component because it is part of another upstream module they employed.

License Risks: A software component or project may not have a license at all, may have one that is incompatible with the component’s or project’s intended use or whose requirements are not or cannot be met.

Immature Software: An open source project may not apply development best practices such as having a standard versioning scheme or lacking a regression test suite, review guidelines or documentation.

Unapproved Changes: A software component may change without giving developers the chance to notice, review or approve such changes because the download link points to an unversioned resource, a versioned resource has been modified or tampered with or due to an insecure data transfer.

Unknown Origin: Details about the source code, build process or the distribution process of a software component may be unknown or non-verifiable.

Endor Labs CEO Varun Badhwar said organizations need more visibility in the potential operational risks that come with increased reliance on open source software. That doesn’t mean organizations should use less open source software, but there are issues that many development teams may not always appreciate. A recent analysis of nearly 2,000 software packages published by Endor Labs, for example, found 95% of all application vulnerabilities can be traced back to a transitive dependency created when a developer employed an open source component.

Regardless of the root cause, responsibility for application security continues to be pushed left toward application developers. The challenge is it’s not possible to achieve that goal without first knowing what issues developers and the DevSecOps teams that support them need to be focused on. Perfect application security is, of course, unattainable, but any reduction in the number of vulnerabilities littering the software landscape will go a long way toward reducing the current level of stress developers and DevOps teams experience.

March 6, 2023
Sysdig Launches Wireshark Foundation

Sysdig this week announced there is now a Wireshark Foundation that will oversee future development of the widely used open source traffic protocol analyzer.

Gerald Combs, who is now director of open source projects at Sysdig, along with Loris Degioanni, CTO of Sysdig, launched Wireshark in 2006 to enable teams to monitor network traffic, learn protocols and packet basics and troubleshoot network problems. There are more than 2,000 contributors and Wireshark has been downloaded more than 60 million times in the last five years alone.

The Wireshark Foundation will provide a framework for long-term stewardship and sustainability. The foundation will be led by Sheri Najafi as executive director, and Janice Spampinato, Hansang Bae, Najafi, Combs and Degioanni will serve on the board.
Combs said rather than donating Wireshark to an existing foundation, it was decided to set one up to formalize many of the community processes that have evolved over the past two decades.

Degioanni said the foundation will also ensure Wireshark remains relevant long after its creators eventually retire. Wireshark has a graphical user interface (GUI) that provides IT teams with an easy-to-understand traffic protocol analyzer. However, as applications become more distributed, additional types of IT professionals, including DevOps teams, are analyzing network traffic. Similarly, cybersecurity teams are using these tools to help track down the source of anomalous activity.

It’s not clear whether network operations (NetOps) and DevOps workflows are merging, but the level of collaboration has increased. As networking increasingly becomes software-defined, it’s clear that developers will employ application programming interfaces (APIs) to manage networks as code in much the same way they do infrastructure in the public cloud. Most of those networking APIs are comparatively low-level, but with the rise of services meshes, it’s clear networking services are becoming more accessible.

The biggest challenge is distinct cultures that have arisen around networking and application development. IT organizations will need to decide whether to provide development teams with the ability to programmatically invoke networking services on their own or through a self-service portal managed by a NetOps team. Regardless of who is responsible for managing the network going forward, the divide between DevOps and NetOps is already starting to narrow. The biggest challenge is simply finding a common language to express core concepts that eliminates any sense of fiefdom that might exist between them. After all, any conflict that arises can usually be attributed to a simple failure to communicate.

In the meantime, in the age of edge computing, network latency issues are becoming even more challenging. An application based on microservices architecture is especially sensitive to network latency issues that are difficult to troubleshoot over an extended network. Tools that make those issues more obvious are crucial.

March 2, 2023
Dev of core-js Will Flip Table ¦ Another 451 PyPI Maldeps

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: Denis Pushkarev is fed up with core-js freeloaders, and hundreds more malicious packages found at PyPI. (more…)

February 16, 2023
Fiberplane Adds Wasm Plug-in Framework for DevOps Notebook

Fiberplane today announced it is extending the reach of a real-time collaboration notebook designed for DevOps teams by making available tools for building plug-ins based on the WebAssembly (Wasm) framework.

Micha Hernandez van Leuffen, Fiberplane CEO, said these plug-ins, dubbed providers, will make it much simpler for anyone to connect the Fiberplane notebook to other DevOps tools and platforms.

The Fiberplane notebook uses the same operational transformation algorithm used in Google Docs to enable teams to easily collaborate around a document or spreadsheet. The core platform itself is built in Rust and WebAssembly. That approach enables a DevOps team to, for example, write and run PromQL queries and display Prometheus charts alongside other data presented via an integrated graph. Wasm makes it possible to run those providers both in the browser and on a backend platform.

Fiberplane also announced it is open sourcing its Provider Development Kit (PDK), written in Rust, to enable organizations or third-party developers to create additional plug-ins. A Fiberplane Daemon then executes the plug-ins. The overall goal is to provide an open format based on Wasm for consuming DevOps data, noted Hernandez van Leuffen.

The full open source Fiberplane WebAssembly-based Plugin System includes a Fp-bindgen to provide the bindings generator for building plug-ins, the Provider Development Kit (PDK), a toolchain for building plug-ins, a set of pre-configured plug-ins for Prometheus, ElasticSearch, Sentry, Grafana Loki, Cloudwatch and a generic HTTP provider, the Fiberplane command line interface and the Fiberplane Daemon.

Fiberplane is essentially taking the concept of notebooks used for collaboration by data science teams and applying it to DevOps workflows. The goal is to improve DevOps teams’ productivity by reducing the amount of time it takes to sort through multiple types and classes of DevOps data to resolve an issue.

As IT environments become more distributed in the age of the cloud and microservices, troubleshooting issues now invariably spans the responsibilities of multiple members of an IT team. Fiberplane, in effect, makes it possible to spin up a virtual war room that enables the members of an IT organization to collaborate until the issue of the moment is resolved.

The speed at which any IT issue is resolved has become a crucial metric. Given the complexity of IT environments, it’s inevitable that incidents will arise. Ideally, IT teams would discover those issues before they disrupt the business. However, in reality, the metrics organizations use to evaluate the effectiveness of a DevOps team are often how quickly IT issues are resolved once they are discovered. The longer it takes for a distributed DevOps team to marshal its resources, the more likely it becomes that team will be perceived as being inefficient—regardless of what level of application availability is actually achieved.

Most DevOps teams have, of course, implemented a wide range of incident management best practices that create a level of muscle memory for responding to a wide range of issues. The trouble is there will always be unforeseen issues that arise. DevOps teams, as a result, need to find ways to quickly focus on an unpredictable issue that they didn’t anticipate.

February 15, 2023
OpenAI Hires 1,000 Low Wage Coders to Retrain Copilot ¦ Netflix Blocks Password Sharing

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: ChatGPT darling OpenAI wants people to write code in English, and the unintended consequences of blocking shared accounts. (more…)

February 2, 2023
Massive Number of Transitive Dependencies Traced to Open Source Code

An analysis of nearly 2,000 software packages published by Endor Labs found 95% of all application vulnerabilities can be traced back to a transitive dependency created when a developer used an open source component.

The study, conducted by the Station 9 research arm of Endor Labs, a provider of a platform for identifying software dependencies, concluded there’s still a 32% chance those software packages would have known vulnerabilities even after components are upgraded to the latest version.

Endor Labs CEO Varun Badhwar said vulnerabilities often remain because the last update made to one of those software components may have been made several years ago even though there are existing known vulnerabilities that affect it. Development teams can’t assume the latest version of a software component is secure, he added.

In general, functional dependencies are created whenever developers download a third-party component, he noted. The most important thing for any software development team to determine when assessing actual risk levels created by those dependences is determining how accessible any given vulnerability is to an attacker regardless of its severity score, noted Badhwar.

In the wake of a series of high-profile breaches, there has been an increased focus on software supply chains. The challenge is most developers don’t have a lot of cybersecurity expertise. They often create patches for applications based on a list of potential vulnerabilities surfaced by cybersecurity teams. The issue, of course, is that just because there is a vulnerability it does not immediately follow that the affected software component can be externally accessed.

Endor Labs is making a case for a graph-based platform that identifies dependencies between the software components that make up an application environment. That approach makes it simpler to prioritize remediation efforts based on the impact a vulnerability might actually have and narrows the current divide between cybersecurity teams and application developers. By the time cybersecurity teams alert developers to a vulnerability they often have moved on to other projects. As a result, developers often lack context because it may have been months since they last looked at the impacted code.

Of course, the inclusion of DevSecOps best practices should improve the overall state of application security as more responsibility for it shifts left toward developers. However, achieving that goal will require more than just giving developers access to software composition analysis (SCA) tools that only surface vulnerabilities in source code as it is being developed, noted Badhwar.

In the meantime, the efforts to remediate all existing application vulnerabilities will be measured in years, so organizations need to determine where to focus their efforts. After all, every minute spent developing and deploying patches is less time that can be allocated to building and deploying new code. The trouble is that as more new code is written, the number of vulnerabilities that could be exploited increases and makes a bad situation worse.

December 12, 2022
How Devs Can Improve Open Source Security in the Enterprise

Modern applications are dynamic. They’re distributed and they’re often born in the cloud. These applications can be developed on the fly, spun up and scaled quickly to meet evolving user and market demands—enabling a level of business agility that allows users to make quick, informed decisions in real-time and take advantage of opportunities as they arise.

Enabling this development velocity are tens of thousands of open source libraries–pieces of code that developers can include in their applications to perform a specific function without having to code it from scratch. Open source libraries prevent developers from having to reinvent the wheel and allow them to focus on their differentiated business logic. While efficient and a major time saver, open source software may be the biggest single threat to software supply chains today. Developers simply have too much faith in the integrity of free, open source code that they casually include and distribute with their applications.

Despite the operational benefits, the pressure to develop quickly shouldn’t expose the organization to increased security risks. Development teams need to rethink how they use open source software and take steps to ensure they meet the same security standards as other enterprise applications.

The Open Source Security Issue

The problem is that most open source projects are maintained by a small number of developers that contribute their time and expertise to build software components that can be reused by the community at large. However, these developers are volunteers who aren’t being paid for their time and effort, nor are they under the same pressure as enterprise developers to ensure there are no vulnerabilities in their code. They may also lack the level of enterprise security expertise necessary to protect applications from increasingly sophisticated attacks. Some may even be hostile to efforts to better secure their code if it means slowing performance or changing the user experience.

The result is that insecure code is increasingly making its way into enterprise applications that use these open source libraries. In fact, the Log4j vulnerability last year was due to a vulnerability in an open source Java logging library. Recognizing the national security importance of open source software, the Biden administration recently issued an executive order and met with cybersecurity professionals to better safeguard the federal government’s computer systems. The resulting recommendations included policies that would help prevent security vulnerabilities in open source packages, improve the process for identifying and fixing defects and reduce time to remediation for distributing and implementing fixes.

It’s imperative that the private sector take notice and make more of an industry-wide effort to secure open source software that makes up businesses’ most critical applications today.

Three Steps for Better Open Source Security in the Enterprise

The bottom line is that enterprises themselves need to take more responsibility for securing enterprise applications—especially as these applications rely more on open source libraries. They need to take a more proactive approach that spans the entire software life cycle, embeds security tools directly into development platforms and provides complete transparency into what makes up their most critical applications.

Here are three things organizations can do to make sure their open source software is secure:

1. Continuously conduct end-to-end application testing

Modern applications are constantly evolving—making it more imperative than ever to continually test for vulnerabilities throughout the entire software life cycle. Starting with the planning stage, security should be embedded throughout the process—providing developers with a solid framework for building secure code before it goes through testing. Once pushed, application security testing should continue as an automatic, built-in step when pushing code to production. DevOps and security teams should work together to ensure security is no longer an afterthought to feature development.

2. Embed enterprise security capabilities directly in development platforms

Forcing developers to take an extra step to ensure secure code when they’re already under pressure to push code quickly is a recipe for failure. Security teams must make it as easy as possible by integrating security controls directly into existing development processes. Standardizing security testing and controls during development makes it more likely policies are recognized, understood and followed.

3. Ensure transparency in every snippet of code you use

Complexity is the enemy of good application security. DevOps teams need to know exactly what makes up their applications—including open source libraries and their dependencies. The federal government is pushing the open source community to standardize a software bill of materials (SBOM). Similar to regulations that require hardware manufacturers to know where every part is sourced, this would force both open source developers and enterprise developers to take more responsibility for the code they include from other sources. That way, if a vulnerability is discovered in a library, enterprises could easily determine if they are at risk and take appropriate action to fully mitigate the issue as quickly as possible.

It’s Time to Take Greater Responsibility

Open source software enables the kind of development agility that makes businesses thrive, but open source also greatly expands enterprise threat surfaces—leaving many organizations at risk of a breach. Organizations need to take greater responsibility for the security posture of the open source libraries they use to speed application development. This requires end-to-end application testing throughout the entire software development life cycle; embedded security tools and controls in development platforms and processes and complete transparency into the open source software that makes up critical enterprise applications. This proactive approach will ensure that vulnerabilities such as Log4j are identified and patched quickly before threat actors are able to exploit them and compromise applications.

December 8, 2022
Why SaaS Vendors Need to Give Back to Open Source

There aren’t many tech organizations that don’t leverage open source technology. Companies that refuse to import software will rely on a freely available library tool or codebase. Open source is one of the largest and most powerful mechanisms of software propagation. However, open source is in danger.

The Two Sides of Open Source Development

In recent years, the ubiquity and dominance of open source tooling have led companies to adopt them en masse. Products like Elasticsearch, Spring and Akka are incredibly popular as open source, freely available tools. But unfortunately, often only one-half of the open source philosophy is being honored.

The Open Source Philosophy

What does that mean? Well, open source depends on two things. Customers use the software and those same consumers contribute to the codebase. It’s a feedback loop of like-minded individuals who have a shared interest in building and using an outstanding product and are happy to donate their time to realize their collective goals. This agreement has driven some of the most exciting software achievements of the past two decades.

Alas, while it became prevalent to use open source software, the popularity of contributions did not scale equally. Suddenly, small teams of dedicated developers were inundated with demands from huge enterprises that equated “open source” with “free.” This caused the owners of open source projects, like Elasticsearch, MongoDB and Akka, to reevaluate their position and change to the increasingly prevalent source available license.

Growing Risk to the Open Source Community

If users contribute to the codebases they leverage, then those codebases can thrive and no one needs to worry about subscription fees or fines. Moreover, users can maintain the certainty that they are not doing anything illegal when they depend on a piece of software. Without contributions from the engineering community, an open source project’s commercial and practical basis quickly disintegrates.

So Why Should SaaS Vendors Give Back?

SaaS solutions inhabit a particular corner of the market, assisting companies in solving a cross-cutting problem. For example, observability. This is an important detail because many open source tools also operate in this arena. This is exemplified by the fact that it’s common for SaaS vendors to regularly compete against an open source, homegrown alternative. Many SaaS solutions actually base their core infrastructure on the same open source software.

This means that SaaS providers are often in direct competition with the open source solutions they leverage to build their product(s).

SaaS Vendors Depend on Open Source Software

The communities that support vital pieces of open source software, like Apache Kafka or OpenDistro, are helping to unlock innovation in enterprises worldwide. The continued pace of this innovation is inextricably linked to the continued growth and development of the open source tooling on which it depends.

The only sensible course of action is for SaaS vendors to make every effort possible to contribute back to the open source space. They do not need to give up their unique features, nor do they need to release their proprietary software, but the simple act of maintaining patches, improving performance, increasing compatibility and even correcting poor documentation—all of this is a contribution that will benefit the entire SaaS ecosystem.

Those Contributions Will Breed Specialization

A big challenge of using open source software is finding engineers that understand how it works. The plug-and-play nature of many tools means that users never need to dive into the details of a library or application. This, however, comes at a cost. Users often don’t know why the software breaks or behaves unpredictably.

If a SaaS vendor begins to contribute back into the core of the open source tools on which they depend, not only are they benefiting their product and the open source community, but they’re also seeding specialist knowledge in their teams. This specialist knowledge means they can utilize open source features in new and exciting ways, giving them insights and advantages over their competitors.

Open Source Contributions Make Commercial Sense

The SaaS community thrives when open source tooling works smoothly. Conversely, if fundamental open source tools like Kafka or OpenDistro begin to falter, then the success of the SaaS community is also at risk. They are highly interdependent. This means a contribution back to core open source tools is a contribution to the stability of SaaS products. Moreover, growing specialist skills within engineering teams means that when it comes time to leverage a new open-source feature, your developers may have skills and insights that other companies won’t have. This is a clear commercial advantage, and all for the cost of doing the right thing, and keeping the dream of free, open source software alive.

December 2, 2022
Securing Open Source Components in a World of Mixed Committer Motivations

Our world runs on software that contains open source components. This places an increased burden on developers, as the primary consumers and deployers of those components, to use code that is fully up-to-date and secure. The vast majority of open source committers with write access to project repositories remain focused on maintaining and making positive improvements to that code, while also helping to benefit the open source community as a whole. However, the sheer complexity of many open source projects has opened the door to different, more insidious and concerted types of attacks which could cause widespread and serious harm.

Developers Have to Move Fast and Reuse Gives Them That Speed

One complicating factor is the prevalence of reuse of third-party open source elements across the majority of open source projects through two main types of dependencies. With direct dependencies, an open source component links straight to a third-party code library, while transitive dependencies occur when a component calls out to a library that is, in turn, communicating with another dependency.

Dependencies enable developers, under ever-increasing corporate pressure to deliver new software rapidly, to move faster by building on top of existing work by their peers. The downside is that those dependency foundations are vulnerable to attack, with some libraries perhaps under the aegis of a single committer for whom the code collection may be a side project and perhaps not attended to on a regular basis.

Sonatype research and that of other organizations tells us that developers working with a Java application may be dealing with a staggering 1,500 dependency changes every year, with the average Java application containing 148 dependencies and the average Java project being updated 10 times annually. While the number of open source projects isn’t ballooning, the amount of versions of those projects is skyrocketing. The majority of vulnerabilities today impacting open source projects result from transitive dependencies, the more complex type of dependency.

In an area where multiple projects may exist effectively solving the same issues, developers need to be aware of which projects are being actively maintained versus those that are either poorly nurtured or no longer in operation. On the other hand, successful open source projects may have tens or hundreds of committers with write repository access, which address a whole different set of issues, including reaching agreement on what a vulnerability consists of and how to fix or patch it.

Amid a Community for Good, Bad Actors and Incidents of Self-Sabotage Emerge

The reasons why individuals choose to commit to open source software are wide-ranging; a strong desire to give back to the community to a passionate and, perhaps very single-minded, hobby to an integral and paid part of a developer’s role and responsibilities at work. A few years ago, the concept of a malicious open source committer was an abstract theory. The thought back then was that perhaps a handful of ‘bad apples’ might exist within a community of millions of developers. However, since 2019, researchers’ tools and those of other organizations have identified over 100,000 malicious, suspicious or proof-of-concept packages, pointing to a much higher degree of behavior by cybercriminals.

Bad actors are deliberately taking advantage of the complexity of open source software to knowingly introduce exploitable vulnerabilities. These attacks are growing in sophistication particularly in relation to malicious code injections into the source code of an open source library. These attacks can often appear as harmless code changes and remain hidden before delivering a malware payload. There is the recent example of a crypto heist that stole over $3 million in cryptocurrency which leveraged compromised access to a private GitHub repository.

Protestware, where a code maintainer chooses to self-sabotage their open source project often to draw attention to a cause, whether geopolitical or specific to that individual, has become an issue over the past year. In this case, although the stated goal is not malicious hacking, real harm, in terms of major disruption, to developers using that code can occur.

To counter both the impact of bad actors and of self-sabotage on open source components, developers need to take advantage of release integrity features to help protect themselves and their organizations from harm. They must be able to have full visibility and control over the software they build and the open source components that they are sourcing as part of that development work. At the same time, governments around the world, including in the U.S., are weighing into issues related to the security of software supply chains, so increased regulations and penalties should also factor into how developers and their organizations behave moving forward.

We’re only one step away from the next potential Log4j attack, and every developer and organization needs to up their game and be ready to move fast on vulnerability identification and remediation. The gathering and sharing of data is what will help to increase everyone’s safety.

December 2, 2022