Search Results: "ana"

30 June 2026

Russell Coker: Dirty Clone and SE Linux

There is a new Linux kernel exploit out named Dirty Clone [1]. The first thing to do to exploit this is to create a container with a separate network namespace via one of the following commands:
unshare -Urn
bwrap --bind / / --unshare-user --unshare-net --uid 0 --gid 0 /bin/bash
The Jfrog people recommend unshare -Urn but I gave the Bubblewrap command as an option as it should work equally well and in some situations may be permitted when unshare isn t. The next step to exploiting it is to use the ip command to set the links up, below is what happens in a user session on a SE Linux system with user_t as the login domain:
# ip link set lo up
RTNETLINK answers: Operation not permitted
That will give an entry in /var/log/audit/audit.log like the following:
type=AVC msg=audit(1782818856.618:3610): avc:  denied    net_admin   for  pid=1829 comm="ip" capability=12  scontext=user_u:user_r:user_t:s0 tcontext=user_u:user_r:user_t:s0 tclass=cap_userns permissive=0
type=SYSCALL msg=audit(1782818856.618:3610): arch=c000003e syscall=46 success=yes exit=32 a0=3 a1=7ffebe5f9e50 a2=0 a3=0 items=0 ppid=1638 pid=1829 auid=0 uid=0 gid=1000 euid=0 suid=0 fsuid=0 egid=1000 sgid=1000 fsgid=1000 tty=pts0 ses=17 comm="ip" exe="/usr/bin/ip" subj=user_u:user_r:user_t:s0 key=(null)ARCH=x86_64 SYSCALL=sendmsg AUID="root" UID="root" GID="test" EUID="root" SUID="root" FSUID="root" EGID="test" SGID="test" FSGID="test"
type=PROCTITLE msg=audit(1782818856.618:3610): proctitle=6970006C696E6B00736574006C6F007570
Unlike previous exploits like Pintheft [2] this doesn t require any really uncommon access to the kernel (unless you consider setting up IPSec to be really uncommon) and is allowed in many container setups. Now on a system with the unconfined module removed (as described in the SE Linux Protection part of my post about Copy Fail [3]) the following domains have such access:
# sesearch -A -c cap_userns -p net_admin
allow container_engine_t container_engine_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow container_init_t container_init_t:cap_userns   chown dac_override dac_read_search fowner kill net_admin net_bind_service net_raw setgid setuid  ;
allow container_kvm_t container_kvm_t:cap_userns   chown dac_override dac_read_search fowner kill net_admin net_bind_service net_raw setgid setuid  ;
allow container_t container_t:cap_userns   chown dac_override dac_read_search fowner kill net_admin net_bind_service net_raw setgid setuid  ;
allow crio_t crio_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow dockerd_t dockerd_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow dockerd_user_t dockerd_user_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow init_t init_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_module sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow iptables_t iptables_t:cap_userns   net_admin net_raw  ;
allow podman_t podman_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow podman_user_t podman_user_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock ipc_owner kill lease linux_immutable mknod net_admin net_bind_service net_raw setfcap setgid setpcap setuid sys_admin sys_boot sys_chroot sys_nice sys_pacct sys_ptrace sys_rawio sys_resource sys_time sys_tty_config  ;
allow spc_t spc_t:cap_userns   audit_write chown dac_override dac_read_search fowner fsetid ipc_lock kill mknod net_admin net_bind_service net_raw setgid setpcap setuid sys_admin sys_chroot sys_nice sys_ptrace sys_rawio sys_resource  ;
allow spc_user_t spc_user_t:cap_userns   chown dac_override dac_read_search fowner kill net_admin net_bind_service net_raw setgid setuid  ;
allow staff_bubblewrap_t staff_bubblewrap_t:cap_userns   dac_override net_admin setpcap sys_admin sys_ptrace  ;
allow sysadm_bubblewrap_t sysadm_bubblewrap_t:cap_userns   dac_override net_admin setpcap sys_admin sys_ptrace  ;
allow user_bubblewrap_t user_bubblewrap_t:cap_userns   dac_override net_admin setpcap sys_admin sys_ptrace  ;
Conclusion It seems that SE Linux configured in the strict mode prevents this exploit in the most obvious use case. But with the range of container related domains that are granted such access it seems quite likely that some configurations and use cases will permit it. Overall the protection that the standard policy for SE Linux can offer (in a non-default configuration) against net_admin access isn t bad, but isn t very good either. I think this will be the first of many exploits based on cap_userns access and that we need to do some work in tightening the SE Linux access controls on such things. One possible way of doing this is to have a program run inside a container in a domain that has permissions such as net_admin to setup the container and not allow domain transitions from the regular programs run in the container (the actual work) to the domain used for network setup. The increasing use of containers by applications is only going to make this problem worse. I think that what we need is something like Flatpak for the vast majority of desktop/phone applications with a container setup program that works with apps packaged in the distribution packaging method (not from Flathub). This is something I m going to investigate for future blog posts.

Utkarsh Gupta: FOSS Activities in June 2026

Here s my monthly but brief update about the activities I ve done in the FOSS world.

Debian
Whilst I didn t get a chance to do much, here are still a few things that I worked on:
  • Leading the DebConf Bursary team along with PEB.
    • This took most of my Debian time this month but we ve been able to wrap that work now.
    • Got back to all the tickets on Zammad, too.
  • Assisted a few folks in getting their patches submitted via Salsa.
  • Mentoring for newcomers.
  • Moderation of -project mailing list.

Ubuntu
I joined Canonical to work on Ubuntu full-time back in February 2021. Whilst I can t give a full, detailed list of things I did, here s a quick TL;DR of what I did:
  • Continued to push for infrastructure improvements:
    • Charming.
    • Artifact signing.
    • Reorganizing cdimage.
    • And so on.
  • Successfully released 26.10 Snapshot 2!
    • We landed a breaking change in the directory structure.
    • whihc had consequences on the rsync, being run by the sysadmins.
      • The 30 GB rsync failed because of the load on the system and it resulted in things blowing up. Yay. Stress-testing the shit out of our infra. :)
      • We got it back under control in the next few days but oh wow, what a journey to get there.
  • Assisted a bunch of folks with my Archive Admin and Release team hats to:
    • Helped in archive opening tasks.
    • Promoting/demoting binaries to/from main.
    • Taking care of package removals and so on.
    • Reviewed the NEW queue.
  • Reviewed quite a lot of MPs, specs, and other people s work.
  • Mentoring, coaching, and leading the Release Management team.

Debian (E)LTS
This month I have worked 15 hours on Debian Long Term Support (LTS) and on its sister Extended LTS project and did the following things:

Released Security Updates

Work in Progress

Other Activities
  • [LTS] Emilio pointed out that the gst-plugins-ugly1.0 binaries were still not fully released, so I ran dcut migrate to fully release them. The DLA had gone out earlier.
  • [ELTS] Did some more work on ruby-rack - a lot of new CVEs have opened up and, whilst I made some progress, Santiago let me know that ruby-rack is no longer supported and so it ll be removed from the ela-needed list.
  • [E/LTS] Set up the security-tracker and a few other things on the new machine, and debugged the git repository size madness. Sent a summary here.
  • [E/LTS] Monitored discussions on mailing lists, IRC, and all the documentation updates.
  • [E/LTS] Attended the monthly LTS meeting on Jitsi. Meeting notes here.

Until next time.
:wq for today.

28 June 2026

Russell Coker: Plaud

While watching a YouTube video I saw an advert for the Plaud AI Note Taker [1]. The Plaud device looks pretty good for what it does, taking notes and managing them, using some sort of LLM function to manage the notes. The devices all cost about $300 which is an amount that doesn t seem unreasonable for someone who s in a lot of meetings. One of the models is the NotePin that seems comparable to the Humane AI Pin I previously blogged about [2]. The business model for Plaud is based on only allowing 5 hours per month of free transcriptions, then charging $16.25/month for 20 hours per month and $33.33/month for unlimited use. That s quite expensive for any serious use. The number of people in the market for an audio recording system that automatically transcribes things may be greater than the number of people in the market for all the stuff that the Humane AI Pin did, but it still may not be enough to run a profitable business when competing with apps on mobile phones. While the product does look decent it seems that they are making the same mistakes as the original Humane developers did, of wanting to lock it down as a subscription based service which reduces the usability of the device. If they had sold an Android hand-held computer with their own app pre-loaded and allowed the user to install a different app then it would have been much more usable. If they had sold Android devices designed for the note taking market and allowed people to choose their own apps to install then their products would have a much longer life expectancy. The majority of Android devices in use are probably out of support but still working while the Humane AI pin can t be used any more and at some time in the not too distant future the Plaud devices will also become unusable. People who buy devices like the Plaud seem to be unaware of the history of such things and the expected future for them. But possibly some people just consider $300 for a year of use to be an acceptable price. If someone wanted to purchase a new high end phone every year and sell their previous one they would probably have a net cost of about $500/year. Maybe I should look for work with a company with an implausible AI based business plan. It would be fun developing such a device if you weren t emotionally invested in the project. Just develop new technology, earn a heap of money, play with fun computers, and move on to the next thing when it collapses. Just like all the Internet companies about 25 years ago.

Russell Coker: Some GPU Stuff

After getting a HP Z4 G4 tower server/workstation to house my Intel Battlemage GPU [1] I ve been playing around with some GPU stuff. For years I ve been just buying GPUs based on the resolution and price and not bothering about anything else due to lack of ability to measure what cards are doing. The nvidia-smi program is really good for NVidia/CUDA setups but I hadn t been aware of anything similar for AMD cards. As I prefer AMD cards for my workstations due to driver issues with NVidia that was a problem for me. I ve recently discovered that the program nvtop (Debian package nvtop) shows the GPU use of multiple GPU types, for me it s worked on AMD and Intel discrete GPUs and shows some information on Intel integrated GPUs, I don t have others convenient for testing at the moment. Currently BOINC has the Einstein@Home [2] project running on the HP Z4 G4 and it s using between 66% and 100% of GPU compute power and 1.6G of GPU RAM. Using 100% GPU compute power allegedly takes 62W of power out of the 190W quoted TDP. I presume that the power use reported by nvtop is very inaccurate. A friend installed a LLM on that system and the libraries used for the LLM were sufficient that BOINC just started using the GPU. On my workstation running an AMD [Radeon RX 460/560D / Pro 450/455/460/555/555X/560/560X] (actually R560) with 4G of GPU RAM I have mpv taking 1G of GPU RAM to play a FullHD video expanded to a full screen window on my 5120*2160 display. I also have about 2G used by the kwin_wayland process (the Wayland server for KDE). That doesn t leave enough GPU RAM to allow Einstein@Home to use the GPU. When playing the FullHD video in question (which is 1.2G for 42 minutes about 500KB/s) at 1.5* speed (a common playback speed I use) that takes about 30% of the compute power on my GPU. I had installed the rocm-opencl-icd package on my workstation (with a 5120*2160 monitor) and restarted boinc-client.service which is all that s needed to allow BOINC to use an AMD GPU. Then the screen started flickering as the Einstein process repeatedly core dumped which I initially assumed to be it s reaction to not having enough GPU RAM available. On every core dump the screen flickered so it went through a process of dozens of screen flickers until it had caused a sufficient number of core dumps and BOINC gave up running that job. Another annoyance is that the boincmgr program (the graphical program for managing BOINC systems) launches two webkit processes that each use about 400M of GPU RAM, so even if other things weren t using all my GPU RAM the boincmgr process would stop the BOINC jobs from using the GPU. I shut down some of the programs that were using GPU RAM until there was 2G free and the BOINC process kept crashing so it seems that there is some other issue. On another system with a 4K monitor there were Chrome and Chromium GPU process taking 1.1G and 500M of GPU RAM respectively and the KWin Wayland process was taking 1G of GPU RAM. So that s well over half the GPU RAM for just browsers and Wayland. With programs like Kitty (terminal emulator) and Nheko (Matrix client) taking over 100M of GPU RAM it seems that 4G is the bare minimum for GPU RAM with modern software and a 4K or similar display. I also noticed the kscreenlocker_greet process taking 440M of GPU RAM. I wonder if a hostile web server could make a web browser take more GPU RAM and starve the screenlocker of GPU RAM, could that allow forcing a screen lock operation to fail? It seems that 4G is the minimum for modern systems, which isn t necessarily a problem as GPUs that are capable of driving 4K displays tend to have no less than 4G. My local computer store has new GPUs with 4G starting at $120 but 12G seems to be the next option up which starts at about $400. Ebay currently has a selection of AMD GPUs with 8G of RAM under $200. I ve had some problems with the GPU in my workstation crashing as described in my previous post where I thought it was driver issues [3]. I now believe that there are hardware issues and will look into buying one of the cards with 8G. Further Investigation I need to determine which of the AMD GPUs that are currently going cheap on ebay are best. While my current PC has support for 150W PCIe power I d rather something less power hungry than that. I have occasional issues of mpv reporting that my system is too slow for a video so slightly more compute power on the GPU would be good, but I think that every available option has significantly more compute power. I need to find out what the relationship is between screen resolution and GPU memory. If I get an 8K display or an array of 4*4K displays (which is quite plausible as 27 4K displays go for $230 each) will I find 16G of GPU RAM as limiting as I find 4G now? The nvtop program tracks PCIe data transfers for AMD GPUs, I haven t yet seen more than 25MB/s and I need to do more tests to see what the maximum is. Running on an Intel Battlemage card nvtop doesn t report PCIe data transfer speed which is a missing feature in either the driver or the program. I need to find out where the problem is and report a bug if someone hasn t already done so. The GPU RAM use of some applications seems excessive. 440M for a lockscreen? 100M+ for a terminal emulator? 320M for Thunderbird?

27 June 2026

Steve McIntyre: It's dead, Jim!

I previously wrote about the upcoming UEFI CA rollover. Well, it's happened now - the old Microsoft UEFI CA from 2011 expired yesterday: Third Party Marketplace Root (used for signing option ROMs and other software)
  Subject: C=US, ST=Washington, L=Redmond, O=Microsoft Corporation, CN=Microsoft Corporation UEFI CA 2011
  Validity
    Not Before: Jun 27 21:22:45 2011 GMT
    Not After : Jun 27 21:32:45 2026 GMT
It's dead - it's not coming back... The world doesn't seem to have ended yesterday, so I guess we did ok? :-) How did we do? After a lot of prodding behind the scenes, Debian and many other distributions managed to get new shim binaries dual-signed with both the old and new CAs. The members of the shim-review team did a sterling job with reviews in the last few weeks. Since I started pushing people in May, we've had 21 reviews accepted successfully - see here for the list. Great stuff! Microsoft have also been working quickly - many of those shim submissions were accepted and signed by Microsoft very quickly too, with a turnaround time of less than 1 day in some cases. Not all of those signed shims have been published and used by the distros involved yet, but expect to see them in the wild in the coming weeks and months. These binaries should be good for people to use for the foreseeable future, until either we need to do another CA rollover or (sadly, more likely) we find an issue in shim that necessitates a new release. What's next? We already have one of our new dual-signed shim binaries in place in Debian, in unstable and testing (Forky) right now. In a couple of weeks from now, we'll be rolling out very similar new dual-signed shim binaries in the next point releases for Debian 12 (bookworm) and Debian 13 (trixie). We'll also be upgrading fwupd in both those point releases, to make DB and KEK updates work better. For more information about these updates, see https://wiki.debian.org/SecureBoot/CAChanges. For your own safety, validate that your systems are updated when possible. If you don't, they may fail to boot in future.

Russ Allbery: Review: The Folded Sky

Review: The Folded Sky, by Elizabeth Bear
Series: White Space #3
Publisher: Saga Press
Copyright: June 2025
ISBN: 1-6680-7812-0
Format: Kindle
Pages: 483
The Folded Sky is a far-future space opera and a fairly direct sequel to Ancestral Night, but with a different protagonist. You do not need to have a vivid memory of the previous book to read this one. It is somewhere around Elizabeth Bear's 31st (!) novel, depending on how one counts and what one includes. Sunyata Song is an archinformist, which is sort of an archaeologist, sort of a librarian, and sort of a historian. She recovers, decodes, and organizes information so that it can be preserved and made usefully available. As the book opens, she is, after an exceedingly long white space journey in an actively hostile ship with a (to Sunya at least) an atavistically off-putting crew, reaching her goal: a vast artifact that I won't describe further to avoid any spoilers for Ancestral Night. She is eager to get to work, an eagerness that is both heightened and made more anxious by the discovery that her academic rival and abusive ex has arrived before her. The pirate attack doesn't help, nor (at least at first) does the surprise appearance of her wife and kids. The opening of this book is a lot of infodumping mixed with nearly stream-of-consciousness emotional dumping. The style shift in this series continues to surprise me; previously, Elizabeth Bear books avoided reader hand-holding to the point of bafflement if you weren't paying close attention. Not here. The Folded Sky takes the shift perhaps too far, and I almost stalled out at the start of this book when Sunya's near-constant self-conscious litany and analysis of fears and concerns started feeling like whining. The book picks up considerably after the attempted murder. About a third of the way through, The Folded Sky feels like it's settling into a recognizable subgenre of murder mystery except set in the far future with fascinating technology and aliens. There has been an attempted murder on a closed station besieged by pirates. There is a law enforcement officer present, but they don't have a lot of investigative experience. For various reasons, Sunya decides to start poking around while being conscious she has no idea what she's doing. The bumbling detective is a common trope, so I thought that was where the story was headed. It is, sort of. There is a mystery and Sunya is involved in solving it. But that's only a small fraction of what's going on, and by the end of the book the plot has shifted firmly back to the genre of space opera, with a side note of family... drama is the wrong word. Whatever one would call a story about raising a rebellious teenager while trying very hard to not turn conflicts into actual drama. I am fascinated by the characterization of this book. Sunya is something of an emotional mess, but Bear doesn't use that fact in the ways that I would normally expect. Similar to Ancestral Night, I finished this book thinking that The Folded Sky is primarily an examination of rightminding, but a more subtle one than the previous novel. Rightminding is a central technology of the White Space series, and I suspect its intended thematic core. Humans in this civilization are equipped with near-universal implants that allow conscious manipulation of one's neurotransmitters and thus emotional state, either by the wearer or by a helpful nearby AI. The fox, the implant used to accomplish this, comes with some other features such as sensory recordings and the ability to load ayatanas (James White style personality recordings to provide some bit of necessary expertise), but rightminding is its primary and most frequently-used function. It is the critical technology that allowed humans to break out of cycles of endless war and join the other peaceful inhabitants of the galaxy in a shared civilization. The name is (intentionally, I assume) Orwellian because Bear knows that many readers, particularly those from the US who have been steeped in simplistic libertarian ideas, will find the idea profoundly creepy. (This was a major plot point in Grail.) This book is not the argument for the technology, though; Bear dealt with that in Ancestral Night. This book is a look at its practical messiness for a person who needs a lot of psychological support. Sunya is anxious, prone to catastrophizing, hates surprises, has some PTSD-style symptoms around space habitats due to earlier trauma, and is also dealing with the unwelcome reappearance of her ex-girlfriend who stole her work. Her first-person narration tends towards insecurity and anxiety spirals, and in another book this might signal an unreliable narrator. In this book, though, there are no dramatic emotional revelations or backstory twists the way there were in Ancestral Night, and the resolution of her troubled relationship with her daughter only partly hinges on plot developments. Instead, Sunya muddles through, with a lot of self-analysis, help from her fox, and a great deal of support from her wife. This makes it sounds like the emotional mess at the start of the book is left unresolved at the end, but that's not true at all. The muddling through works! Sunya keeps doing things that I thought were foreshadowing some catastrophe, but she knows herself better than the reader does. Bear largely avoids the sudden ruptures that are normally used to resolve emotional problems in fiction. Instead, Sunya spends a lot of time and energy working on her thinking and her relationships while trying to be ethical and useful, and those efforts slowly bear fruit. I'm worried this makes the book sound boring; rest assured that it isn't. This emotional subplot is only an undercurrent in the novel, and the main plot has enough weird science, alien aliens, and space opera drama to satisfy my page-turning desires. I'm focusing on the emotional arc in this review because I find it so unusual and so oddly compelling, particularly in retrospect. This is not how one normally does emotional development in a novel. Sunya's fox and rightminding aren't even the focus except when the pirates express their typical libertarian disgust for the idea. Rightminding is an entirely normal part of Sunya's life that she relies on. It doesn't solve all of her problems, but it gives her a foundation from which to tackle them in the slow and frustrating and inconsistent way that is required outside of novels, via a long series of small decisions to be the person she wants to be. I think The Folded Sky will be more hit and miss for readers than the other books of this series. Sunya was, for me at least, a much harder character to like early in the book, and it takes quite a while for the plot to get going. But this is one of those books that I've not stopped thinking about since I finished it. I think it makes a fascinating pair with Ancestral Night. The first book makes the philosophical argument for rightminding, and this book shows the practical reality with all of its messiness. The Synarche has some significant flaws (including the status of AIs, which is another interesting subplot), but it's a workable system. It feels rare to read a science fiction novel that shows this level of messiness without pairing it with an argument for radical change, and as frustrating as it was to read in places, I am intrigued by the overall effect. Sometimes acknowledging problems and working on them within an existing framework works. Followed by a book tentatively titled Shipwreck Star that does not yet have a release date. Rating: 7 out of 10

26 June 2026

Jonathan Wiltshire: Streamlining Debian Updates with AI: The Stable Update Adviser

Please consider supporting my work in Debian and elsewhere through Liberapay.


Some months ago I started working on a small experiment: a specialised LLM assistant for Debian maintainers preparing proposed updates for stable and oldstable.

The aim is not to replace review by the Stable Release Managers, nor to automate away maintainer judgement. It is meant to be a pre-advice tool: something maintainers can use while they are still preparing a proposed update, before sending it to other people to review.

If you ve uploaded to stable before you may have some experience with our acceptance criteria. Does the version sort correctly? Is the changelog clear enough? Is the delta focused? Are the patches documented? Are the right bugs or CVEs mentioned? Are they of sufficient severity? What is the risk to users of stable? Is there an ABI change hiding in the diff?

These are the sort of checks where a structured first pass can be useful, provided it is treated as advice rather than authority.

To explain what the tool does, what could be more appropriate in an AI age than to ask it?

Describe yourself and your abilities and limitations for a blog post.

It answers:

I m Debian Stable Update Adviser, a specialised ChatGPT assistant for Debian maintainers preparing proposed updates for Debian stable and oldstable.

My main job is to review a single .debdiff and give practical, policy-aware feedback before a maintainer submits or uploads a proposed update. I focus on whether the update appears suitable for Debian stable or oldstable, especially under the Stable Release Managers expectations for minimal, targeted, low-risk changes.

I can inspect a debdiff for Debian changelog quality, including suite, version, bug references, CVE mentions, and rationale. I can check version correctness using Debian dpkg version semantics. I can review packaging changes under debian/, such as patches, maintscripts, symbols files, conffiles, Build-Depends, autopkgtests, and control metadata. I can also group upstream source changes into behavioural and non-behavioural categories, and flag areas that may carry regression risk.

My reports are intended to be concise and useful to maintainers. A typical review includes a quick summary, behavioural and non-behavioural change breakdown, mechanical policy checks, risk assessment, stable-policy checklist, acceptance likelihood, rationale, maintainer advice, and a clear conclusion.

My limitations are important. I cannot prove that a package builds, that tests pass, that the bug is fully fixed, or that the Stable Release Managers will accept the upload. I also do not replace maintainer judgment, archive review, autopkgtest results, reproducibility checks, or real-world upgrade testing. I can only review the provided debdiff and point out likely issues, risks, and improvements.

I also do not proceed without a valid debdiff. The whole point of my review is to assess the actual proposed delta, not to speculate from package names or bug descriptions alone.

In short, I act as a focused pre-review assistant for Debian stable and oldstable proposed updates: useful for catching policy, versioning, changelog, packaging, and regression-risk issues early, but not a substitute for the Debian review process itself.

That last point is an important one. This is not an oracle, and it is not part of the Debian archive machinery. It is a checklist with some language-model assistance, aimed at reading a debdiff and pointing out things that might be worth another look.

I know that commercial AI and LLM tools are not universally welcome in Debian. That is understandable. Debian depends on transparency, human responsibility, licensing clarity, and technical correctness. LLMs have obvious problems in all of those areas. They can be wrong, and worse, they can be wrong in a fluent and plausible way. They are impossible to reproduce and their training is opaque.

But I see this as a useful first pass for a maintainer who is unused to working in stable, and would benefit from a virtual mentor giving their proposal a quick check and reassurance. Perhaps they don t have a more experienced co-maintainer to ask. Perhaps they are conscious that stable reviews are presently a two-man effort and want to avoid adding round trips to that load. Perhaps they just need some reassurance.

So despite my reservations I am today opening the adviser up for general use, and I m interested in feedback about how it responds to real world proposals in various states. Most of the examples I have tested with already had a green light, so the value added by the adviser is limited. I would especially be interested in seeing a transcript alongside the submitted debdiff.

Try it out

I would dearly love to build this in a more Debian-ish environment, but for now I m limited in resources and skill to do that (help is welcome). Until that s a reality, you can try out the ChatGPT implementation: Debian Stable Update Adviser

Russ Allbery: Review: Platform Decay

Review: Platform Decay, by Martha Wells
Series: Murderbot Diaries #8
Publisher: Tor
Copyright: 2026
ISBN: 1-250-82701-9
Format: Kindle
Pages: 245
Platform Decay is the eighth book in the Murderbot science fiction series. You absolutely should not start here, but you also don't need to remember the specifics of the previous books. As the story opens, Murderbot and a friend (the identity of whom is a spoiler for previous books) are infiltrating a Corporation Rim torus, a massive space station that encircles a mined-out planet. (Like most science fiction megastructures, this is more space than the plot really requires.) Murderbot's mission is to exfiltrate some of Dr. Mensah's family members who have become entangled in corporate shenanigans. The corporates are eager to get revenge for the events of System Collapse, not to mention the other times Preservation Station has upended corporate plans. Murderbot's job is to stop them. The group, in addition to one of Dr. Mensah's partners, includes an older woman and a young child. Murderbot is analytical and of course not at all emotional about children, which is reliably a good time. Also, the older woman is gruff, stubborn, and thoroughly enjoyable. There are, of course, complications that lead to picking up more children and going through rather more of the torus than Murderbot wanted to explore. Each section of the torus is run by a different corporation and has a different constructed environment and visual aesthetic, so there are a lot of opportunities for fights, daring escapes, and incidental trouble. Also, well:
So I had installed a mental health module. I know, I was surprised I did it too.
After the events of System Collapse, University Medical decided that Murderbot needed a bit more metal health support.
The only reason I agreed to it was that the mental health module didn't actually try to adjust my processing or core programming or anything; it just monitored my organic neural tissue. When my neural tissue started to generate weird chemicals and whatever, it would ping me to "check in with my emotional state." Seriously, I could have coded that myself. (I told Dr. Bharadwaj that, and she said, "Would you have ever coded that yourself?" which was totally unfair and also correct. I would never have done that.)
Speaking as someone whose neural tissue sometimes generates weird chemicals and whatever, I sympathize. The specific form this module takes is periodic "emotion check" parentheticals throughout the narration, which I found utterly delightful.
I ran that through risk assessment and it produced the equivalent of a shrug. (Emotion check: Shrug sigil right back at you, you piece of shit.)
This is otherwise an extended action movie sort of a book, much like several of the early novellas. There are no major political or interpersonal developments here and the usual cast (apart from Murderbot) is mostly absent. Instead, we get an extended, dangerous journey through a corporation-controlled habitat, mixed with Murderbot trying to interact with humans in a way that minimizes its annoyance while being hopefully reassuring. It's competence porn with awkward but surprisingly heartfelt emotional bonding, not that Murderbot in any way wants to bond or would appreciate that description. I doubt this will be anyone's favorite entry into the series since there are none of the big reveals or major leaps of character development there have been in the past few books. But, like all Murderbot books, the narrative tone is wonderful and all of the small asides and little moments of character interaction are an utter delight. If you've gotten this far in the series, you know what I mean and you'll be as happy to read more of it as I was. There is a part of me that is hoping for some major plot development, and I always want to see more of ART (who has no significant role in this book), but Wells has the narrative style down so perfectly that I would read and enjoy a book about Murderbot doing just about anything. If you're this far in the series, you probably don't need a review, and since this is an action-heavy adventure rather than a character growth novel, I don't have a lot more to add. There's a new short Murderbot novel out and you want to read it. Recommended to everyone who enjoys the series. Rating: 8 out of 10

21 June 2026

Tim Retout: seL4 repo relationships

The seL4 organisation on GitHub uses git-repo to manage multiple source repositories, and so there are a large number of projects to get your head around when figuring out the ecosystem. As an experiment, I have taken the various manifest files across the org, and constructed a graph based on how frequently each pair of repositories is mentioned in a manifest together. See below: Graphviz Diagram [This may render badly when syndicated outside of my blog; and also on small screens. And probably large screens. I ve attempted to make sure there s a non-JS fallback on my site with JS enabled, if you hover over a node, it should highlight connected nodes.] The colouring of the nodes is mostly manual; I experimented with graph clustering algorithms but have not found a satisfactory result so far. Still, some clusters are obvious: It s quite hard to pull apart the CAmkES framework and the core libraries; there are definitely some which are more associated with VM management, but the overall shape of this co-occurence data is a messy ball in the middle with some outliers in orbit. One observation is that camkes is correctly identified as more peripheral than camkes-tool, which contains the actual core CAmkES code. Reflecting on this approach, in hindsight I m surprised that using co-occurences worked as well as it did there was no attempt to actually inspect the code and find direct mentions of other code e.g. library header dependencies. As the newer microkit effort largely eschews git-repo, better results might be found by actually taking that more detailed approach, so that graph edges could represent real dependencies between two packages. Additionally, this could allow diving into the various libraries held in the different libs repos, to get a more granular graph of relationships between them. However, I think I spent more time on making it possible to render graphviz graphs easily on my blog than actually gaining any insight into the codebase!

20 June 2026

Russell Coker: Font Sizes

The Problem In 2019 I blogged about getting a 4K monitor because of my vision being inadequate for a 2560*1440 monitor [1]. Now I m using a 40 5120*2160 monitor [2] and still trying to find the correct balance between how much I want to see on the screen and what I am physically capable of seeing on screen. Currently Kitty is my terminal emulator of choice [3]. What I most like about it is the feature of having multiple terminal windows in a single OS window, so instead of having 9 or 16 different xterm instances running all with possible alignment issues I have a single window for all terminals which can be brought to the foreground. The impending 6.7 release of KDE (my favourite Linux desktop environment) [4] includes the feature of per-screen virtual desktops which might be the feature I need to make multiple monitors usable for me. One of the factors stopping me from using multiple monitors in the past was the issue of not getting the alignment of dozens of xterms right if a monitor goes to sleep mode and is regarded as disconnected, moving a few Kitty windows is much easier than moving dozens of xterms (also a tiling window manager isn t my style). I ve just decided that the Terminus font (my favourite out of the monospaced fonts in Debian) is too small for me at 9.0 point. But then I tried 10.0 which looked really ugly and an experiment showed that 10.5 looked good. What I ve Learned This is the best explanation I ve seen of how ridiculous the whole font point thing is [5]. It doesn t and won t ever correlate to pixels. So what we ideally want to do is set the size on screen to match the actual pixel size of the font. I can t find any software to interrogate a font file and find out what sizes it supports. The web page for the Terminus font says that it supports 6 12, 8 14, 8 16, 10 18, 10 20, 11 22, 12 24, 14 28 and 16 32 [6]. So the question is how to get a terminal program that uses one of those. Kitty doesn t and won t support specifying font size by pixel. I tried some other terminal programs, I started with the Debian Wiki page TerminalEmulator [7] which wasn t very helpful, I added some new entries to that page. There doesn t seem to be another option for a terminal emulator with multiple terminals in one OS window that can arrange them automatically. I didn t even get to the stage of checking whether other terminal emulators supported font size in pixels. The lcdf-typetools package contains the program otfinfo which gives some interesting information on fonts but nothing about the font sizes in pixels. Sites like Coding Font to compare fonts [8] can never work properly as the fonts will always be slightly different sizes as the same point size doesn t mean the same display size. The Current Situation On my 5120*2160 monitor with 9 Kitty terminal sessions with 9.0 point font they each have 277*50 characters. With 10 point it s 237*46 but fuzzy and unpleasant to read. With 10.5 point it s 208*43 which isn t as good as I m used to but is still almost 4.5* as many characters as the original 80*25 standard for terminals. Some time before 2019 I had a 4*4 array of terminal windows that were 100*25 or 120*25. That left some space at the right and bottom so I could open another 8 or 9 terminals that were partially obscured if I needed to. By 2019 before getting a 4K monitor I had a 3*3 array of terminal windows as my standard desktop and a larger monitor that did 4K resolution allowed me to have 16+ terminals again. Now with Kitty I routinely have 9 terminals in a 3*3 array and I can easily open more if I need them and have them resize appropriately. This situation works reasonably well, but the element of just trying different sizes in 0.5 point increments until I find something that looks good is unpleasant. I should be able to specify the next largest increment of the bitmaps in the font and just have it look good. Conclusion It would be good if more people tested the terminal emulators in Debian and added information to the wiki page about them. The current page is useful but needs more information to support the variety of features that people find important. We need some tools to provide information on fonts in Debian, such as the sizes of bitmapped fonts. The whole point size thing is just wrong and would ideally go away. The vast majority of font use nowadays is for things that will probably never end up on a printed page so trying to map it to a physical size in fractions of an inch makes no sense. But that s just one of many horrible things used for backwards compatibility that aren t going to go away any time soon. Really everything involving inches should go away.

Gunnar Wolf: systemd for Linux SysAdmins

This post is a review for Computing Reviews for systemd for Linux SysAdmins , a book published in Apress
systemd. Yes, in full lowercase. If there was ever a technology to cause controversy in the Linux world, this is it. Since its inception in 2010, systemd s goals were set quite high: to replace the vital part in every Linux system that takes care of the system boot process. It quickly reached maturity, allowing it to be adopted as the main init system in most major distributions just five years later. Despite describing events that happened over a decade ago, systemd adoption still raises the temperature in any Linux-related discussion. David Both s comprehensive book tackles the what, why, and how issues surrounding systemd. Carefully divided into 16 chapters, going from the basics and some of the technical and political history behind the project to the different subsystems and aspects covered by systemd, its almost 450 pages can scare people away. But the text is written in a very clear, tutorial-like fashion, and while it can be read sequentially, cover-to-cover, readers can also pick a single aspect and jump straight to the relevant chapter. A frequent criticism of the systemd project is that it aims to basically rewrite all of a Linux system, and just looking at this book s index shows there is some truth to it. The first chapter is an introduction to the systemd project and a brief overview of its history (including the controversies around it), and the following four chapters deal with understanding and controlling the system boot process. That leaves ten chapters to cover different aspects or subprojects of systemd, such as time and date issues (synchronization, time specifications, and controlling repetitive tasks), understanding and leveraging the system journal that strongly departs from the old syslog system, network configuration and firewall management, system health and performance debugging all aspects that in the traditional Unix philosophy were managed by independent programs. And I can identify several systemd subprojects not covered by this book! We long-time Unix and Linux administrators took pride in how highly performant and stable systems were supported by the simplicity of our tools; systemd critics point out this massive project has absorbed dozens of individual tools, yielding corporate control over vast swaths of vital system tooling. Truth is, as a sysadmin myself, systemd is today one of my greatest allies. I appreciate how the author evaluates every component independently, including his personal evaluation of each even acknowledging when he prefers working with the traditional programs. If I had to note one criticism: given the many console captures, having a maximum width below 70 characters means several lines are unnaturally cut short (and continued with odd indentations). There is probably no right way to solve this, but it does affect the reading experience.

19 June 2026

Wouter Verhelst: Agentic coding and Free Software

Through work, I have paid license to windsurf (recently renamed to "devin"), an application for LLM-based (aka, "Agentic") development. I hadn't been using it that much, but in an effort to more clearly understand how this whole AI development thing works, I decided to give it a closer look recently. My conclusions: In its current form, this whole LLM wave is problematic for multiple reasons. But ignoring that, and looking at the technology only, I can say that:

Problems Lest someone (incorrectly) assume that I am arguing in favour of the current state of affairs with regards to LLMs, let me state this first. The way LLMs are built today is highly parasitic. Websites are downloaded in whole, at unsustainable rates, regardless of the consent of the people who made the original content. The result is predictable: servers get overloaded, server administrators attempt to implement various mitigations. Some of these mitigations work; some do, for a while; some are entirely useless. In actual fact, the mitigations are an arms race -- if too many people implement the same mitigation, then the people who try to build yet another LLM so they can extract rent will just try to work around the mitigation, eventually they will succeed, and you'll just have to come up with another mitigation. It's a bit like spam; you introduce regex-based spam filters, they introduce spelling mistakes, you introduce bayesian filters, they add a large batch of markov chain-generated semi-nonsense words made invisible by markup, you add filters to block emails with such markup, they move the text into an image. We have working mitigations today, but eventually we'll run out of ideas. LLMs glob up everything they can while ignoring the license of the source material. The people who push those LLMs claim that pushing the source material through the machine learning algorithms makes the output of the algorithm distinct enough from the source material that the license no longer applies; I'm not so sure that this is true. I guess the New York Times v OpenAI lawsuit will teach us some of the answer to that question here, but even so the ethical questions about "is it OK to bring down another server just so we can download the internet for another for-pay LLM" are still open. And regardless of what the law states, my opinion on "you're using my copyleft code to generate code under a different license" is not something you might like if you agree with the rent seekers' opinion on the subject. That all being said and true, the technology works. You can have a "conversation" with an LLM that resembles a human one. If you pass it some data, you can use plain english to ask it questions about that data, which is a lot easier than to ask it about that in a formal way. You can request it to generate some code, and it will generate something that looks like what you need and that will be mostly correct for like 95% of the time. Now, yes, 95% of the time is not 100% of the time, and no, you can't ask it to "write me a piece of software that implements this 300-page requirements document and get back to me when you're done", because it will fail, and you won't know where it has failed, and you'll take it into production and expect everything to be fine because it won't and this one minor logic bug will cause half your servers to spin and consume credits with your infrastructure provider with nothing to show for it. But that doesn't mean you can't use an LLM to build a large piece of software. It just means you have to understand the LLMs limitations and strenghts, and use them correctly. Here's what an LLM is good at:
  • Generating plausible text
  • Interpreting text to figure out what a plausible meaning or summary of that text is
  • Giving vague indications as to what the probable context of a given body of text is.
It turns out that that's enough to use the LLM to build a reliable piece of software, provided you do it right.

Paradigm shift An LLM can generate text by the truckful. The generated text could be code. Given a good enough LLM, the generated text might even run and do something useful. You can try to blindly run the code, and if it doesn't run correctly, you can paste the error message to the LLM, and it can tell you what went wrong and how you could possibly fix it. This creates a feedback loop: you ask it for an amount of code, you run the code, you receive an error, you tell it that the code is problematic and give it the error message, it makes changes to the code, now you have something that at least no longer fails at startup. If you ask it to add tests to make sure that your code acts as per your specification, now you get an error if and when the code doesn't act as per your specification. Or, well, at least not as per the part of the specification that was correctly turned into a unit test by the LLM. LLMs have a context window, so if the error message is pasted in the same conversation as where the code was generated, it is able to reuse the earlier prompts to refine how it should interpret the error message that you received. You can't really paste the source code of an entire application into the prompt of your LLM, that would quickly overrun its context window. But LLMs also allow you to provide some form of background information -- a document, say -- on which you ask it to reason. It will interpret that document, but doing so uses less of the LLMs context window. So providing the LLM with your application's source code as background information can help it understand better how your code interacts. This is especially helpful if you only provide the LLM the background information relevant to the actual question. So now if you are able to:
  • Create background context with your application's source code
  • Have the LLM generate a first draft of your requested change, plus the tests to make sure it works
  • Compile (if applicable) the generated code (and tests) and run said tests
  • Return any error messages to the LLM with a request to correct the error
Then the combination of "getting it 95% right off the bat" and the above feedback loop means you can generate syntactically correct code, that probably does what you need, in minutes. I say "probably" for a reason. There are going to be cases where you specify a request without a number of details (because they are implied), and the LLM will get most of those details right but just not implement the one bit because it's an automaton and it doesn't think. Or you will ask it to make sure that two bits of the application look exactly the same, without specifying that they must act the same, now and in the future, and it will just generate the same block of code twice and then in a future change it will change one but not the other. But if you review the changes, and you have experience as a programmer, you will be able to spot most cases where the LLM got it wrong. And so it's possible, if not necessarily easy at first, to use an LLM to generate mostly correct code. There are certain places where "mostly correct" code is not desireable. But equally, there are also cases where, "mostly correct" is good enough. After all, most of the software you run today -- the bits of it that weren't, yet, generated by an LLM -- is only "mostly correct", too, because to err is human and we all make mistakes. If not, there wouldn't be any CVEs and your software would never do anything wrong. Now, doing the feedback loop described above is certainly something you could do manually. You could open an account on one of the LLM websites, upload the source code of your application, ask it to generate some new feature, download the newly generated feature, run it, and then copy/paste any error messages back into the LLM. But that's a lot of manual work of the type that computers are pretty good at. So that's what the "windsurf" tool helps you with: you run it inside your IDE -- either a VSCode-based tool that you download from their website which comes with their product preinstalled, or a separate JetBrains plugin that you can install. You can then open your entire relevant codebase in a workspace in your IDE. You then ask the LLM, through the IDE, to generate a new feature in your codebase, and to also generate the test while it's at it. It will use a mixture of LLM interpretation and non-LLM functionality to scoop out the relevant bits of your codebase to send to the LLM as background information, will send it your prompt, will download the generated code and patch or create files, will compile (if required) and run the newly generated code and tests, and will refine the generated code if the tests produce any errors. All mostly automatic; by default, running anything requires explicit confirmation. You can turn that off completely (probably not a good idea), or you can give it a whitelist of things that you don't want to confirm (perhaps OK), and the tool also passes standing instructions to the LLM to never generate any command that deletes a file (which, like with any LLM, can be overridden, but it requires you to be very stubborn and to use more credits than you'd probably like). All this put together means you can build something without writing any piece of code, provided you do it right.

A technically positive evolution Don't go and say, "here's a 300-page document, read it and write whatever the document says". It will get it wrong, it will write a massive test suite that it will only run at the end, it will choke itself up trying to interpret the massive amount of failures it encounters, it will fill up its context window and it will start to forget some of the requirements. That won't work. But what you can do -- what I did, in fact -- is this. First, create an empty workspace. Don't put any code in it. Then, tell the LLM to generate a backend framework using technology X and a frontend framework using technology Y that initially only says "hello, world". Also add tests to it, and run the tests. It will do that. You'll not get much, but it will work. Then, ask it to add some UI elements. A login page, perhaps. A navigation bar. Small things. Most of it doesn't have to be functional -- but tests must be there for the bits that are, and have it run the tests and evaluate the results. Rinse, repeat, until you have a working application. Importantly, in between the steps, you should also run the application yourself and see if the change was implemented correctly. Sometimes it won't be. Sometimes there will be a subtle bug -- I at one point had a the application hang after a few minutes. Sometimes you tell it that there's a subtle bug, and it will discover it more quickly than you could, and it will fix it, and in implementing the fix it will uncover another bug, and then you have to fix that one -- the fix it came up with for the hang was to move something to an async process on the server, which caused the application to start spinning while trying to create hundreds of async jobs (this is when I realized that the hang was a deadlock due to some part of the codebase doing something that indirectly triggered itself). Sometimes it will try to fix the bug you tell it about, and you'll see that it's going off on a tangent that has nothing to do with what you're seeing. It's important to keep an eye on what it's doing, so you can guide it back on track when that happens -- when I told it about the hang, it started investigating the part of the code which sends out emails, thinking that it could hang while waiting for sendmail to finish, but the hang was happening when the application was idle, not when it was sending out emails, and only when I told it about it happening when it was idle did it find the deadlock. So it's not a fully automatic process, and it needs to be guided by someone who knows what they're doing. But if that is the case, you can come up with something that works. I spent evenings and breaks for about a week, and I managed to create a working application which, had I written it by hand, would have taken me a few months of full-time work to come up with. And I now have a side project, fully complete and working, that I had been thinking about doing for more than a decade, but never got around to actually doing, because of all the work that would be involved and I just didn't see myself having the time for. It's not perfect code. But it's mostly good enough, and it will perform the job it needs to. And it looks far slicker than most of the side projects I've done in the past, because in the past I would prioritize between implementing new features or making something look slick, and I would decide that the new feature was more important because it's only for me and there's only me and nobody cares if it looks good or not and I don't have three weeks to come up with something that looks better. But here, I found myself sometimes spending 10 minutes writing a prompt with instructions on making things look better. Because what's 10 minutes when you just spent an hour writing down and refining specifications for functionality and tests? There are a number of other things in which an LLM can help a programmer. For instance. I received a bug report recently in a project I'm paid to maintain that I couldn't make heads or tails of. I opened the source code in my windsurf IDE, pasted the bug report in the prompt, and then requested the tool to analyze the source code and the associated logs and tell me how the described behavior could be happening. It turned out that I had overlooked something, but with the help of the tool, I found the bug in minutes. I was trying to understand a particular part of a large codebase that I didn't really grasp very well. I loaded the codebase in the tool, and asked it to explain to me how a particular action is performed by the code. I requested specific functions and line numbers. I now have a far better understanding of how the code works, and will be able to write that patch that I've been wanting to write for years -- without using the LLM. I have been struggling for, literally, years with understanding why another tool that I maintain was misbehaving in a particular way but only in Firefox. I opened the codebase in Firefox, explained the buggy behavior in plain English, and asked it to explain how this could be happening. It picked up some obscure corner case behavior of ffmpeg and mp4 containers that I was not aware of and that perfectly explained why things were misbehaving in the way that they were. At the same time, there are limitations. Giving an LLM a codebase that was originally generated by an LLM (either the same one or another one) seems to work well. Giving it a codebase that was written by a human and expecting it to correctly update it seems to be more error-prone. I did one or two of those as a trial, and it is more problematic than anything. An LLM is also not intelligent, notwithstanding the popular term of "Artificial Intelligence". On multiple occasions, I've asked it to write a test case for some code that was not set up to do so; and rather than suggesting a refactor is required, it would instead copy the code that needed to be tested and then test the copy, rather than the original. The tool has made multiple similar errors. I have sometimes people describe agentic coding as "similar to interacting with junior programmers", but that is not the case. A junior programmer will either fill in the gaps in your specifications, or ask for clarification when something seems off. The LLM will not do that; it will do what you ask, exactly that and nothing more. If you missed a corner case in your specification, then all bets are off. I remember learning about programming language generations in college. A first-generation language is "machine code", a second-generation language is "assembler", a third-generation language is any high-level language such as C, Perl, or Pascal. I've forgotten what set a 3rd-generation language apart from a 4th-generation language. But I remember the definition they gave me for a 5th-generation language: "you tell the computer what to do, and it will do it". At the time, I thought it was ridiculous. Nobody could ever write something like that. But it's here. And it's a threat to free software.

A threat to free software? Yes. There is the obvious part where most of the well-known LLMs are non-free software. I mean, there are some "open source" LLM models. The windsurf tool that I used doesn't allow you to use them (directly), but they're there. There are also open source applications that implement what the windsurf editor does. So it's definitely possible to work like this without resorting to non-free software and non-free services, even though the non-free LLMs might be a bit ahead of the curve of the free ones. But that's not what I mean. And there is also the obvious thing which I mentioned earlier in this post, which is that the people who try to build LLMs are doing it in unethical, disgusting ways, causing downtimes and disregarding licenses for whatever they can get their grubby hands on. Ideally we wouldn't be in that situation, and ideally this wouldn't be a problem, but we are where we are. And there's the obvious thing where the OSI sold itself out and declared that a machine learning program can be open source even when the very things it was built from -- the training data -- is not available. That's a major issue that the free software community needs to fight against, but there's not really anything that that is a threat to free software. You just build your own, free software, LLM, and you're done. The actual threat is in funding and developer support. Most large businesses do not care about free-as-in-freedom software. They like the free-as-in-beer part, and they appreciate that the free-as-in-freedom bits can make the software more customizable. They are (mostly) happy to do sponsorships of the free-as-in-freedom projects that they use if that means their free-as-in-beer usage of the software gets improved. But why would you care about all that when you can just generate the code you need, rather than interacting with an open source community that may or may not care about your business's interests?

Where to go from here Although I think the moral and environmental issues with LLMs are real and problematic, given the experiments I did I am not convinced that the concept of interacting with a computer system in natural language and to use it to generate code is necessarily deficient. There are pitfalls, but they can be managed. It is possible to use such a system to create throwaway, proof-of-concept type "good enough" code bases. It can be used to interpret code bases and to understand bug reports. I believe that the major issue with LLMs has to do with that saying about hammers and nails:
If all you have is a hammer, then everything looks like a nail.
LLMs are an outgrowth of machine learning, pushed by large corporations. These large corporations have a lot of money. If all you have is money, then every problem can be fixed by throwing more money at it. The initial language models were promising but not (yet) good enough, and it seemed that one way in which they could be improved was to increase the scale of the statistics: throw more hardware (and thus money) at it, and rather than improving the efficiency of the models, just scale up. Scaling up is something that megacorporations are very good at. It's only a money problem, after all. Does that mean that "scaling up" is the only way to improve the models, though? I'm not convinced. Some hardware, such as most modern Apple and Samsung devices, ship with accelerator hardware for machine learning algorithms. There are some models that are small enough to be able to run on these devices. I don't see why it should not be possible to create a small(er) language model that can do some useful part of the above-described use cases; if not locally, then at least on a server that one can run on-prem rather than requiring that you pay rent to one of the LLM companies. The Software Freedom Conservancy has published an aspirational statement on machine learning-assisted programming that, I think, gets a lot right. It's not quite a definition, but it's something to keep in mind. Perhaps that's the way forward? More questions than answers at this point, anyway.

Freexian Collaborators: Monthly report about Debian Long Term Support, May 2026 (by Santiago Ruano Rinc n)

The Debian LTS Team, funded by Freexian s Debian LTS offering, is pleased to report its activities for May.

Activity summary During the month of May, 21 contributors have been paid to work on Debian LTS (links to individual contributor reports are located below). The team released 56 DLAs fixing 877 CVEs. May was a much busier month than usual, especially due to the disclosed vulnerabilities on linux regarding Local Privilege Escalation (LPE), that included public proof-of-concept (PoC) exploits. These reports of course impacted Debian as a whole, and the situation warrants a special mention to the Kernel Team, especially Ben Hutching and Salvatore Bonaccorso, who faced the pace and released linux packages on a weekly basis. On the LTS side, the Front Desk team also triaged a significant flow of high severity CVEs. It is also important to note that Debian 12 ( bookworm ) will be handed over to the LTS Team on June 11th. If you benefit from Debian, especially during the full 5-year lifecycle, please consider subscribing as a sponsor of Debian LTS: https://www.freexian.com/lts/debian/. Moreover, Debian 11 ( bullseye ) will reach the end of the Debian LTS period on August 31st. After that, Freexian will continue the security support under the Extended LTS offer. The team published several notable updates:
  • As mentioned above, several exploitable LPE vulnerabilities in linux were published during May. Ben released the following DLAs for the Debian LTS versions:
  • exim update (DLA-4580-1), prepared by Thorsten, to address a vulnerability that may result in remote code execution.
  • gnutls28 update (DLA-4595-1) by Guilhem Moulin, fixes several vulnerabilities that may result in execution of arbitrary code, information leak, authentication bypass, among other impacts.
  • krb5 updates released as DLA-4603-1, fixing two vulnerabilities that may yield to a denial of service. Updated prepared by Emmanuel Arias
  • lemonldap-ng (DLA-4602-1), released by Abhijith PA, fixing multiple vulnerabilities
  • Two imagemagick updates (DLA-4559-1 and DLA-4609-1), prepared by Bastien Roucari s, fixing several vulnerabilities
  • openjdk-11 and openjdk-17 updates (DLA-4566-1 and DLA-4565-1), both prepared by Emilio, to fix seven vulnerabilities.
  • php7.4 update (DLA-4586-1) to fix six vulnerabilities that could result in remote code execution, information disclosure or denial of service. Update prepared by Guilhem Moulin.
  • python3.9 update (DLA-4583-1), prepared by Arnaud Rebillout, addressing multiple vulnerabilities.
Contributions from outside the LTS Team: We are greatly thankful for the contributions from people outside the LTS Team:
  • Colin Watson prepared an OpenSSH update, that was released by Santiago as DLA-4584-1.
  • Thomas Goirand handled a keystone update, whose advisory was done by Santiago and released as DLA-4611-1.
  • Christopher Obbard kindly prepared a sentry-python update, released as DLA-4612-1.
  • Christoph Goehre made two thunderbird updates (DLA-4562-1 and DLA-4582-1). As is customary, Emilio released the advisories.
The LTS Team has also contributed with updates to the latest Debian releases: Moreover, thanks to our partnership with Catalyst, it has been possible to extend the support for Samba 4.17, the version shipped with Debian 12. In May, several vulnerabilities were disclosed, and their patches were prepared by Catalyst. For Debian 12, the update was prepared by the Samba maintainer and released as DSA-6297-1.

Individual Debian LTS contributor reports

Thanks to our sponsors Sponsors that joined recently are in bold.

16 June 2026

Vincent Bernat: Building a Soviet Nail Factory: how KPIs killed efficiency

In 2008, I landed my second job, in the network team at Orange Portails1, the division behind the websites and search engine of the French telecom operator Orange. The place ran like clockwork: a comprehensive technical setup, a dedicated team for every part of the business, and room to focus on what I do best. A few years later, none of that mattered: thanks to an obsession with the numbers, we could no longer deliver new services on time.

Disclaimer This is a story I like to tell to warn people about Goodhart s law.2 As these events happened almost 15 years ago, my recollection is a bit fuzzy. I left in 2012.

The first years During my first years, the department operated like a startup. Its cradle was the French company Echo. They built a search engine. France T l com bought it and renamed it Voila. It was the most visited search engine in France in the early 2000s. France T l com consolidated the portal activities into the Wanadoo Portails division, later renamed Orange Portails. The technical environment was excellent. We had many internal tools:3 a ticket system, an RRD-based graphing tool, an IPAM, a reporting tool, and an SNMP-based alerting tool.4 We deployed our Linux servers with CFEngine. We installed systems and applications from internal Debian repositories. We documented everything in a private MediaWiki instance. Supervision was performed with an ancestor of Xymon. The network architecture was clean and scalable with little legacy. We onboarded new people in a day. It was a nurturing environment for me. I developed several tools: lldpd, an 802.1AB implementation, Snimpy, a pythonic binding for Net-SNMP, Wiremaps, a layer-2 discovery tool with a time machine to know which device is connected where, Kit r , a tool to simulate network conditions, QCSS-3, a controller for load-balancers, and ipoo, a service available through a Jabber chatbot and a Greasemonkey script to expose IP-related information. I added SNMP support for Keepalived and Quagga. I also started this blog, with articles like Anycast DNS, TLS-related articles like TLS computational DoS mitigation, SNMP-related articles like Integration of Net-SNMP into an event loop, Linux-related articles like Tuning Linux IPv4 route cache, and an article about VXLAN long before it was cool.

The collapse When we needed new servers, the on-site team would take a set from the inventory, install our base Linux distribution on them, put them in the datacenter, and cable them to the top-of-the-rack switches. We opened a ticket describing the servers we needed, and one week later, our servers were available. Orange wanted to know if this team was performing well, so they asked for KPIs. They decided to use the number of tickets completed in a year. They asked to double this number. So instead of one ticket for a new service, we would open six tickets one per server. By the end of the year, the KPIs had more than doubled. Everybody saw it as a success for performance management. So, they asked to do the same for the next year. Now, we needed to open a ticket per server and per step. Again, the KPIs doubled. Behind the scenes, the tickets went to different people and were no longer handled in order. So, for the next year, it was decided to have meta-tickets and meetings to follow the progress of these tickets. Of course, all these extra steps pushed the KPI even higher. This performance management method spread to the other teams.5 Everything became slower. Instead of a couple of weeks, a new service now took six months. We built a Soviet nail factory. But the KPIs were good, and we stopped caring. Let me give you another example. We had to estimate the impact of each night operation. We weren t half bad: we declared most operations without any expected impact. Most of the time, there was no impact. One time out of five, there was a 5-second impact. We were told to try harder to meet our expected impact. What did we do? We started declaring a 5-second expected impact. One day, we got a 30-second impact and were told we failed to match the expected impact. In the end, we declared most operations with a 10-minute expected impact, and we stopped caring: instead of carefully shifting traffic around, we allowed ourselves a 5-minute impact. And our KPIs were never better.
Graph showing the impact of night operations. Year after year, the impact tolerance has been increased. In the final year, the expected impact is 10 minutes, and all operations remain under this threshold. However, the impacts are much more significant than they were in the first year.
An artist's rendering of the evolution of impacts over the years.

KPIs are not bad, but they are easy to break. Use them carefully: let the people doing the work help choose the metrics, and tie those metrics to the quality of the service for example, with service level objectives. Otherwise, even dedicated people stop caring, game the system, and eventually quit.6

  1. Internally, this division was named Hebex. It was located in Bagnolet (next to Paris) and Sophia-Antipolis (near Nice).
  2. Goodhart s law often gets the credit, but Campbell s law describes my experience even better: the more you lean on a number to make decisions, the faster people corrupt it.
  3. At the time, SaaS was not really a thing. I remember we considered, with a couple of colleagues, selling Wiremaps as a SaaS, with homomorphic encryption for the database. But who would outsource their observability stack?
  4. Snalert was a metacircular alerting tool in Perl. It was able to poll a very large number of SNMP targets in a short timespan. All our monitoring was SNMP-based, including system monitoring.
  5. My team also managed the rules of many Linux-based firewalls. To increase our KPIs, we used the same method: rather than accepting one ticket with a flow matrix, we requested one ticket per flow.
  6. Orange is not unique. Google s promotion process is another well-known example of a broken KPI. Michael Lynch explains it in Why I Quit Google to Work for Myself.

15 June 2026

Freexian Collaborators: Debian Contributions: Go default compatibility, Trimming build-essential, Python upstream engagement and more! (by Anupa Ann Joseph)

Debian Contributions: 2026-05 Contributing to Debian is part of Freexian s mission. This article covers the latest achievements of Freexian and their collaborators. All of this is made possible by organizations subscribing to our Long Term Support contracts and consulting services.

Go default compatibility, by Helmut Grohne At the MiniDebConf Hamburg, Andrew Lee had prepared a talk on how Debian accidentally chooses Go compatibility. Helmut joined Tobias Quathammer and Andrew Lee in looking into the problem. Go has a compatibility system where modules declare a desired Go version to be compatible with. This influences various features such as whether RSA keys smaller than 1024 bits are accepted. Unfortunately, Debian s way of building Go packages is unique in setting GO111MODULE=off, which practically implies a very old compatibility version that enables a number of insecure settings. Most Linux distributions use the default GO111MODULE=on and therefore consult a go.mod file that often declares a sensible version. While doing so is the way for Debian longer term, getting there involves major changes so we also sought a more short term workaround. We developed a patch to the Go compiler that would enable it to pick up a compatibility version from the environment. Tobias uploaded it to unstable. The next step is communicating the declared compatibility version from go.mod to the compiler via the new variable. Then, rebuilding the archive resolves the immediate symptoms. This does not save us from having to perform the larger transition to GO111MODULE=on, but this shortcut can be backported to trixie.

Trimming build-essential, by Helmut Grohne One of the harder problems of the architecture cross bootstrap is correctly expressing the Build-Depends of glib during the toolchain bootstrap. It implicitly depends on build-essential, which happens to depend on libc6-dev. This poses a cycle. It applies even for cross building, because it is interpreted for the host architecture and that there is no way of satisfying this dependency during the toolchain bootstrap. Given discussions at MiniDebConf Hamburg with Jochen Sprickerhof and others, a seemingly stupid idea evolved: Let s delete build-essential. What looks insane on the surface might deserve a second look. Given how we moved away from C, C++ and autotools, what is in build-essential no longer is required by much of the archive. With the rise of debputy, debian/rules no longer has to be a makefile. While the task would be huge, those packages relevant to architecture bootstrap could explicitly support building without the implied dependency making their dependencies explicit. In a number of cases, this amounts to issuing a dependency on g++-for-host. This dependency requires the use of architecture-prefixed tools. Therefore, Helmut wrote a debhelper change that makes it always pass build tools to various build systems. This also enables more packages to honour environment variables such as CC and CXX.

Python upstream engagement, by Stefano Rivera Stefano attended PyCon US (at personal expense) to improve upstream relations and ensure Debian s voice is heard where it needs to be. On Friday there was a packaging summit (notes) with good discussion on the future of the wheel format, and some discussion of the new abi3t shared library format for free-threaded python. In preparation for the event, Stefano did a complete review of the current patch stack. Stefano s primary goal was to get some of Debian s patches merged during the sprints, and results were mixed. Some trivial patches (e.g. GH-150098, made progress and merged, but the most consequential patch Debian is carrying is still blocked. Stefano will continue to try to drive progress on this.

Miscellaneous contributions
  • Carles worked on po-debconf-manager: Reviewed Catalan translations for 6 packages, submitted 10 packages to maintainers, and removed 3 packages from po-debconf-manager.
  • Carles worked on check-relations: Continued improving the backend, including importing source package build dependencies to better support analysis of Debian blends. Added support for ignoring packages using regular expressions and source package names in response to user feedback. Used the tool to report 5 new bugs and followed up on previously reported issues.
  • Helmut sent a cross build patch on behalf of a customer.
  • Helmut uploaded debvm and guess_concurrency both featuring improved reproducibility and documentation.
  • Helmut continued maintaining rebootstrap and made it correctly handle binNMUs of gcc-defaults. Additionally, he poked at existing gcc patches giving answers, rebasing or closing them.
  • Helmut supported the video team in Hamburg mixing audio.
  • Helmut continued to report undeclared file conflicts of various kinds and corresponded with maintainers about them.
  • Antonio attended a debate during the Brazil Internet Forum about the impacts of the child protection regulation (ECA Digital) on free software operating systems.
  • Antonio worked on Debian CI to improve the system transparency for users. This included listing any pending jobs explicitly in the job lists for each package/architecture/suite page, as well as adding a queue status page that users can check for an estimate of test latency.
  • Antonio worked on several Debian CI maintenance tasks, including but not limited to some monitoring improvements, replacing usage of fonts-font-awesome with fonts-fork-awesome, and adding the ability in debci to configure a global notice (which is being used in Debian CI to point to the system status pages).
  • Antonio started doing some tests related to the change of default Debian CI backend from lxc to incus-lxc. This helped identify an omission in the creation of incus-lxc images. It was missing dpkg-dev, which caused a few packages that assumed its presence to fail. In the end, the incus-lxc backend will be fixed to include dpkg-dev by default in the image, but that uncovered an undeclared dependency in gem2deb (Ruby packaging helper) and in ruby-byebug, both already fixed in unstable.
  • Stefano did some minimal work on debian-reimbursements to get it working with current versions of django-allauth.
  • May included the discovery of several high-severity Linux kernel root exploits. Stefano updated kernels and rebooted debian.social infrastructure several times.
  • Stefano supported the Hamburg miniDebConf s wafer website during the event, and set up an instance for the 2027 edition too.
  • Stefano supported the bursary team issuing bursaries for DebConf 26.
  • Stefano uploaded routine updates of python-pip, pystemmer, snowball-data, snowball (making up a mini, uncoordinated snowball transition), python-authlib, python-discovery, python-installer, python-mitogen, python-pipx, python-cachecontrol, platformdirs, and python-virtualenv.
  • Stefano fixed a small number of bugs in dh-python, culminating in the 7.20260524 upload.
  • Thorsten finally managed to upload a new upstream version of hplip. He also uploaded a new upstream version of epson-inkjet-printer-escpr. Last but not least with the help of other contributors he could fix bugs in lprng.
  • Lucas and Santiago contributed significantly to the DebConf 26 Content team; helping to organize the team, review and rate talk proposals.
  • Lucas also supported a packaging sprint held in India by rebuilding and publishing the latest results of the Ruby 3.4 transition effort.
  • Santiago continued contributing to the efforts to organize DebConf 26, especially supporting the local team with different tasks.
  • In collaboration with Emmanuel Arias, Santiago is mentoring Aryan Karamtoth, a GSoC participant that is working to introduce linux live-patching support in Debian. The GSoC project started in May, with community bonding and coding. Santiago reviewed a merge request to prepare the clang-extract package for debian. clang-extract is one of the building blocks that will help to extract specific functions from large C code, so only relevant code can be patched, without recompiling the whole original basecode.
  • Anupa assisted Jean-Pierre Giraud with the point release announcements for Debian 13.5 and Debian 12.14.
  • Colin backported various security fixes from OpenSSH 10.3 to all supported releases (including LTS and ELTS).
  • Colin backported IP quality-of-service fixes to OpenSSH in trixie. The situation there had been unsatisfactory for some time, and upstream reworked their QoS support in OpenSSH 10.1 in a way that typically produces much better results.
  • Colin imported new upstream versions of 26 Python packages, and fixed around 25 RC bugs for the Python team.

14 June 2026

Matthias Klumpp: Introducing pkgcli: A nicer command-line interface for PackageKit

For almost two decades, the PackageKit package management abstraction layer has shipped with pkcon as its command-line client. pkcon does its job, but it was always kind of a testing front-end for the PackageKit daemon rather than a tool designed for everyday use. The focus has instead been on the GUI tools, automatic system updates, GUI application managers and other front-ends. Its command names mirror the D-Bus API almost one-to-one (get-details, get-updates, get-depends), output is very plain, and there is no machine-readable mode for scripting. Most importantly though, there has been no development on it at all for almost a decade, so pkcon was stuck in its rudimentary state from that era.

Since a lot of changes will be coming to PackageKit, and testing the daemon and working with it from the command-line was not very pleasant anymore in 2025/2026, I decided to modernize the tool as part of my work as fellow for the Sovereign Tech Agency last year. pkgcli is the new command-line client for PackageKit. It is built from the ground up to be pleasant to use interactively and easy to drive from scripts.

Why a new tool?

Of course, instead of introducing a new tool, I could have just expanded pkcon instead. The problem with that approach is that the pkcon utility has been around for so long and its command-line API had ossified so much, that rather than changing it and potentially breaking a lot of scripts relying on its quirks, I decided to introduce a new tool instead. pkcon can still be optionally compiled for people who need it in their scripts and workflows.

The goals for pkgcli, and the features it now has are:

  • Human-friendly command names. Verbs that read the way you d describe the task, instead of mirroring the D-Bus API 1:1: show, search, list-updates, what-provides, instead of get-details and friends.
  • Readable, colored output by default (still respecting NO_COLOR and degrading gracefully).
  • A real scripting mode. A global --json flag emits JSONL instead of fully human-readable output when possible, to make it easier to use the tool for scripting purposes.
  • Sensible defaults. A few defaults have been changed, such as the metadata cache-age, or automatic cleanup of unused dependencies being enabled by default. This is more in line with current defaults by other tools and frontends. We also print package information in a slightly different, more readable way.
  • Better handling of internationalized text. Text should now align properly in the terminal window, and we should no longer have completely chaotic text output on non-English locales (especially Chinese/Japanese).

Why not pkgctl?

Originally, this tool was called pkgctl, to match other common cross-distro tool names. However, that name was already taken by an Arch-specific distro development tool. When this issue was raised, we decided to just rename our tool to pkgcli with the next release, to avoid the name clash on Arch Linux.

Examples!

Here are some examples on how to use the new tool (some of which include the abridged output pkgcli prints).

Search for anything containing the string editor in name or description, then look at the details of one result:

$ pkgcli search editor
Querying                  [ ] 100%
  ace-of-penguins 1.5~rc2-7.amd64 [debian-testing-main]
  acorn-fdisk 3.0.6-14.amd64 [debian-testing-main]
  ardour 1:9.2.0+ds-1.amd64 [debian-testing-main]
  audacity 3.7.7+dfsg-1.amd64 [manual:debian-testing-main]
  audacity-data 3.7.7+dfsg-1.all [auto:debian-testing-main]
  augeas-tools 1.14.1-1.1.amd64 [debian-testing-main]
  emacs 1:30.2+1-3.all [debian-testing-main]
  gedit 48.1-9+b1.amd64 [debian-testing-main]
  gedit-common 48.1-9.all [debian-testing-main]
  gedit-dev 48.1-9+b1.amd64 [debian-testing-main]
[...]
$ pkgcli show nano
Package: nano
Version: 9.0-1
Summary: small, friendly text editor inspired by Pico
Description: GNU nano is an easy-to-use text editor originally designed as
 a replacement for Pico, the ncurses-based editor from the non-free mailer
 package Pine.
[...]
URL: https://www.nano-editor.org/
Group: publishing
Installed Size: 2.9 MB
Download Size: 646.0 KB

Search only within package names rather than descriptions:

$ pkgcli search name python3

Check for updates. refresh updates the metadata, then list-updates reports what s available:

$ pkgcli refresh && pkgcli list-updates
Loading cache            [ ] 100%
  cme 1.048-1.all [debian-testing-main]
  gir1.2-gdm-1.0 50.1-2.amd64 [debian-testing-main]
  imagemagick 8:7.1.2.24+dfsg1-1.amd64 [debian-testing-main]
  imagemagick-7-common 8:7.1.2.24+dfsg1-1.all [debian-testing-main]
  imagemagick-7.q16 8:7.1.2.24+dfsg1-1.amd64 [debian-testing-main]
  libdlrestrictions1 0.22.0.amd64 [debian-testing-main]
  libfftw3-bin 3.3.11-1.amd64 [debian-testing-main]
  libfftw3-dev 3.3.11-1.amd64 [debian-testing-main]

Explore relationships between packages:

$ pkgcli list-depends inkscape  # list what inkscape depends on
$ pkgcli list-requiring libappstream5  # list what requires libappstream5

Find the package that provides a capability, here the AV1 GStreamer decoder:

$ pkgcli what-provides "gstreamer1(decoder-video/x-av1)"
  gstreamer1.0-plugins-bad 1.28.3-1.amd64 [auto:debian-testing-main]

You can also have JSON output for most commands! Attach --json to any query and pipe the result straight into jq. Each line is a self-contained JSON object:

$ pkgcli --json list-updates   jq -r '.name'
cme
gir1.2-gdm-1.0
imagemagick
imagemagick-7-common
imagemagick-7.q16
libdlrestrictions1
libfftw3-bin
libfftw3-dev
libfftw3-double3

Try it

pkgcli is built by default alongside the rest of PackageKit since PackageKit 1.3.4. If your distribution ships a recent enough PackageKit, it should already be on your PATH. You can read its man page man pkgcli for more information. Feedback, bug reports, and patches are very welcome.

13 June 2026

Gunnar Wolf: Rey Ubu - Carro de Comedias, UNAM

Today we went to see a theater play in UNAM s Cultural Center, very near our home. No, not inside any of the theaters in the square just between Sala Nezahualc yotl, Foro Sor Juana and Sala Carlos Ch vez.. So, yes, not only we had fun, but we had fun for free! Announcement UNAM s El Carro de Comedias is an itinerant theater company that often presents in this same spot (but you can see the stage is foldable, and they do have presentations elsewhere, of this same play even). I went with my family, and we enjoyed a very fun adaptation of this great play (written by teenager Alfred Jarry in 1894). One of those plays that could be inspired any day by current geopolitical events I know most of the people that happen to stumble upon my blog are not in Mexico City. But if you happen to be here, do consider going to their function. Check their schedule; being it an itinerating show, they can also be found at other places, but they are scheduled at the same place we saw them, every Saturday and Sunday until June 28, 11:00AM. They mentioned they will likely continue during August, but AFAICT it is not confirmed (or, at least, announced) yet. Some pics, shot randomly by me throughout the play: Announcement First_call Accordion Mom Announce Plotting Audience Wenceslao Attack Grumpy Ministers Council Message Russian Soldiers All End

12 June 2026

Mike Gabriel: Ayatana Indicators: Call for Translations

In the process of preparing a major Ubuntu Touch release (v24.04-2.0, coming soon...) we will also update Ayatana Indicators in Ubuntu Touch. Last week various new features have been added to some of the indicators (toggle switch to keep the display switched on permanently, blue tooth pairing agent, redesign of the keyboard indicator, etc.) and those changes require translation updates. If you can, please visit [1] this weekend and help translating Ayatana Indicators into your native language. Thanks so much!!! light+love
Mike [1] https://hosted.weblate.org/projects/ayatana-indicators/

10 June 2026

Mike Gabriel: Future of libayatana-appindicator (v0.6.0 released today)

Some of you might have noticed that the recent (or rather: previous) version of libayatana-appindicator (v0.5.94) notified users and developers of the library being deprecated. This short post is to notify you, that with today's libayatana-appindicator v0.6.0 release [1] this deprecation warning has now been removed again. Another new feature (added to AppIndicator without ABI breakage) is tooltip support. The new package version has just been uploaded to Debian experimental. Please test if your application (if it gets linked against libayatana-appindicator) continues to work flawlessly. Thanks! libayatana-appindicator will receive continued support until GTK-3 becomes end-of-life (because libayatana-appindicator has a baked-in GTK-3 dependency which should not be ported to GTK-4 imho). That said, in the future, GTK-3 applications can continue using libayatana-appindicator for sending AppIndicator-like icons and menus over DBus to KStatusNotifierItem-based system tray renderers. If you are looking for an AppIndicator implementation for GTK-4 applications (or other), I'd like to encourage you to help making libayatana-appindicator-glib [2] a new standard (can be used in GTK and Qt applications alike, implementation is using pure Glib-2.0). Currently, there is only one renderer (ayatana-indicator-application), so more work needs to be done on the renderers' side. (One of the next work items here is to get AppIndicator-Glib support working in Lomiri's desktop/windowed mode). [1] https://github.com/AyatanaIndicators/libayatana-appindicator/releases/ta...
[2] https://github.com/AyatanaIndicators/libayatana-appindicator-glib/

Colin Watson: Free software activity in May 2026

My Debian contributions this month were all sponsored by Freexian. You can also support my work directly via Liberapay or GitHub Sponsors. OpenSSH I backported various security fixes from 10.3 to trixie, bookworm, bullseye, buster, and stretch. For trixie, I also backported several IPQoS fixes to line up with upstream s traffic management settings and drop a rather hacky Debian-specific patch; this needed a quick follow-up fix. I upgraded trixie-backports to 10.3. I fixed openssh uses pidof but does not depend on procps. PuTTY I upgraded from 0.83 to 0.84. Python packaging New upstream versions: Other build/test failures: Other bugs: I updated python-treq upstream to stop vendoring multipart, now that the packaging issues with that have been sorted out. Code reviews Other bits and pieces I contributed a debian-policy patch to fix several links related to build profiles.

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