10 Apr 2026

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Reproducible Builds: Reproducible Builds in March 2026

Welcome to the March 2026 report from the Reproducible Builds project!

These reports outline what we've been up to over the past month, highlighting items of news from elsewhere in the increasingly-important area of software supply-chain security. As ever, if you are interested in contributing to the Reproducible Builds project, please see the Contribute page on our website.

  1. Linux kernel hash-based integrity checking proposed
  2. Distribution work
  3. Tool development
  4. Upstream patches
  5. Documentation updates
  6. Two new academic papers
  7. Misc news

Linux kernel hash-based integrity checking proposed

Eric Biggers posted to the Linux Kernel Mailing List in response to a patch series posted by Thomas Weißschuh to introduce a calculated hash-based system of integrity checking to complement the existing signature-based approach. Thomas' original post mentions:

The current signature-based module integrity checking has some drawbacks in combination with reproducible builds. Either the module signing key is generated at build time, which makes the build unreproducible, or a static signing key is used, which precludes rebuilds by third parties and makes the whole build and packaging process much more complicated.

However, Eric's followup message goes further:

I think this actually undersells the feature. It's also much simpler than the signature-based module authentication. The latter relies on PKCS#7, X.509, ASN.1, OID registry, crypto_sig API, etc in addition to the implementations of the actual signature algorithm (RSA / ECDSA / ML-DSA) and at least one hash algorithm.


Distribution work

In Debian this month,

Lastly, Bernhard M. Wiedemann posted another openSUSE monthly update for their work there.


Tool development

diffoscope is our in-depth and content-aware diff utility that can locate and diagnose reproducibility issues. This month, Chris Lamb made a number of changes, including preparing and uploading versions, 314 and 315 to Debian.

In addition, Vagrant Cascadian updated diffoscope in GNU Guix to version 315.


rebuilderd, our server designed monitor the official package repositories of Linux distributions and attempt to reproduce the observed results there; it powers, amongst other things, reproduce.debian.net.

A new version, 0.26.0, was released this month, with the following improvements:


Upstream patches

The Reproducible Builds project detects, dissects and attempts to fix as many currently-unreproducible packages as possible. We endeavour to send all of our patches upstream where appropriate. This month, we wrote a large number of such patches, including:


Documentation updates

Once again, there were a number of improvements made to our website this month including:


Two new academic papers

Marc Ohm, Timo Pohl, Ben Swierzy and Michael Meier published a paper on the threat of cache poisoning in the Python ecosystem:

Attacks on software supply chains are on the rise, and attackers are becoming increasingly creative in how they inject malicious code into software components. This paper is the first to investigate Python cache poisoning, which manipulates bytecode cache files to execute malicious code without altering the human-readable source code. We demonstrate a proof of concept, showing that an attacker can inject malicious bytecode into a cache file without failing the Python interpreter's integrity checks. In a large-scale analysis of the Python Package Index, we find that about 12,500 packages are distributed with cache files. Through manual investigation of cache files that cannot be reproduced automatically from the corresponding source files, we identify classes of reasons for irreproducibility to locate malicious cache files. While we did not identify any malware leveraging this attack vector, we demonstrate that several widespread package managers are vulnerable to such attacks.

A PDF of the paper is available online.


Mario Lins of the University of Linz, Austria, has published their PhD doctoral thesis on the topic of Software supply chain transparency:

We begin by examining threats to the software distribution stage - the point at which artifacts (e.g., mobile apps) are delivered to end users - with an emphasis on mobile ecosystems [and] we next focus on the operating system on mobile devices, with an emphasis on mitigating bootloader-targeted attacks. We demonstrate how to compensate lost security guarantees on devices with an unlocked bootloader. This allows users to flash custom operating systems on devices that no longer receive security updates from the original manufacturer without compromising security. We then move to the source code stage. [Also,] we introduce a new architecture to ensure strong source-to-binary correspondence by leveraging the security guarantees of Confidential Computing technology. Finally, we present The Supply Chain Game, an organizational security approach that enhances standard risk-management methods. We demonstrate how game-theoretic techniques, combined with common risk management practices, can derive new criteria to better support decision makers.

A PDF of the paper is available online.


Misc news

On our mailing list this month:



Finally, if you are interested in contributing to the Reproducible Builds project, please visit our Contribute page on our website. However, you can get in touch with us via:

10 Apr 2026 4:13pm GMT

Jamie McClelland: AI Hacking the Planet

A colleague asked me if we should move all our money to our pillow cases after reading the latest AI editorial from Thomas Friedman. The article reads like a press release from Anthropic, repeating the claim that their latest AI model is so good at finding software vulnerabilities that it is a danger to the world.

I think I now know what it's like to be a doctor who is forced to watch Gray's Anatomy.

By now every journalist should be able to recognize the AI publicity playbook:

Step 1: Start with a wildly unsubstantiated claim about how dangerous your product is:

AI will cause human extinction before we have a chance to colonize mars (remember that one? Even Kim Stanley Robinson, author of perhaps the most compelling science fiction on colonizing mars calls bull shit on it).

AI will eliminate all of our jobs (this one was extremely effective at providing cover for software companies laying off staff but it has quickly dawned on people that the companies that did this are living in chaos not humming along happily with functional robots)

AI will discover massive software vulnerabilities allowing bad actors to "hack pretty much every major software system in the world". (Did Friedman pull that directly from Anthropic's press release or was that his contribution?)

Step 2: To help stave off human collapse, only release the new version to a vetted group of software companies and developers, preferably ones with big social media followings

Step 3: Wait for the limited release developers to spew unbridled enthusiasm and shocking examples that seem to suggest this new AI produce is truly unbelievable

Step 4: Watch stock prices and valuations soar

Step 5: Release to the world, and experience a steady stream of mockery as people discover how wrong you are

Step 6: Start over

Even if Friedman missed the text book example of the playbook, I have to ask: if you think bad actors compromising software resulting in massive loss of private data, major outages and wasted resources needs to be reported on, then where have you been for the last 10 years? This literally happens on a daily basis due to the fundamentally flawed way capitalism has been writing software even before the invention of AI. A small part of me wonders - maybe AI writing software is not so bad, because how could it be any worse than it is now?

Also, let's keep in mind that AI's super ability at finding vulnerable software depends on having access to the software's source code, which most companies keep locked up tight. That means the owners of the software can use AI to find vulnerabilities and fix them but bad actors can't.

Oh, but wait, what if a company is so incompetent that they accidentally release their proprietary software to the Internet?

Surely that would allow AI bots to discover their vulnerabilities and destroy the company right? I'm not sure if anyone has discovered world ending vulnerabilities in Anthropic's Claude code since it was accidentally released, but it is fun to watch people mock software that is clearly written by AI (and spoiler alert, it seems way worse that software written now).

Well… we probably should all be keeping our money in a pillow case anyway.

10 Apr 2026 12:27pm GMT

Reproducible Builds (diffoscope): diffoscope 317 released

The diffoscope maintainers are pleased to announce the release of diffoscope version 317. This version includes the following changes:

[ Chris Lamb ]
* Limit python3-guestfs Build-Dependency to !i386. (Closes: #1132974)
* Try to fix PYPI_ID_TOKEN debugging.

[ Holger Levsen ]
* Add ppc64el to the list of architectures for python3-guestfs.

You find out more by visiting the project homepage.

10 Apr 2026 12:00am GMT