How GitHub and PyPI Are Using Time to Stop Supply Chain Attacks

Michael Miller · 2026-07-26

If you've been following the world of software development, you know that supply chain attacks have become a real headache. They're like a thief breaking into a house through a window you didn't even know was open. But now, GitHub and PyPI (Python Package Index) are fighting back with a clever new trick: time-based defenses in Dependabot, their dependency management tool. Let's break down what this means for you and your projects. ### What's the Big Deal with Supply Chain Attacks? Supply chain attacks happen when someone sneaks malicious code into a software package that you rely on. Think of it like a trusted delivery service bringing you a package that's actually a bomb. These attacks can spread fast because one compromised package can infect thousands of projects that depend on it. That's why GitHub and PyPI are stepping up their game. The new mechanism they've introduced uses time as a shield. Instead of just checking if a package is new or updated, Dependabot now looks at when a package was published or changed. If something was added too recently, it raises a flag. This gives the community time to review and catch any bad actors before you pull the trigger on an update. ### How Time-Based Defenses Work Here's the simple version: Dependabot now has a built-in delay. When a new version of a package appears, it doesn't automatically recommend it. Instead, it waits for a certain period. This is like a cooling-off period for software updates. It might be a few hours or days, depending on the package's history and how much trust it's earned. - **New packages** get a longer waiting period because they haven't proven themselves yet. - **Frequent updates** from trusted sources get a shorter delay, but they're still checked for suspicious timing. - **Abnormal patterns** like a sudden flurry of updates from a previously quiet maintainer get extra scrutiny. This approach isn't perfect, but it's a smart layer of defense. It forces attackers to either wait longer (which increases their risk of being caught) or move faster (which makes them easier to spot). ### Why This Matters for Developers If you're a developer using Python or GitHub for your projects, this change is good news. It means you get an extra safety net without having to do anything extra. Dependabot will now automatically flag or delay suspicious packages, giving you time to check if something's off. But here's the catch: you need to keep your tools updated. If you're running an old version of Dependabot or ignoring its warnings, you're missing out on this protection. Make sure you're on the latest version and actually paying attention to those alerts. ### The Bigger Picture: A Shift in Security Thinking This move shows a bigger trend in cybersecurity: moving from reactive to proactive defenses. Instead of just cleaning up after an attack, companies like GitHub and PyPI are trying to prevent them from happening in the first place. Time-based defenses are a simple but powerful idea because they exploit one thing attackers can't control: time itself. Other platforms might follow suit. We could see similar features in package managers for JavaScript (npm), Ruby (RubyGems), or even container images on Docker Hub. The idea is catching on because it's cheap to implement but hard to bypass. ### What You Can Do Right Now First, update your Dependabot configuration. Make sure you're using the latest version and that time-based checks are enabled. Second, review your dependency list. Are there packages you haven't touched in months? Consider removing them to reduce your attack surface. Third, stay informed. Follow security blogs or set up alerts for your key packages. Remember, no defense is 100% foolproof. But by combining time-based checks with good practices like code reviews and testing, you can make your projects much harder to compromise. And that's a win for everyone.