Eviction Notice: Reviving and Advancing Page Cache Attacks
snee.la
Foreword This blog post is a summarized and introductory write up of our paper recently accepted at NDSS 2026, “Eviction Notice: Reviving and Advancing Page Cache Attacks”. Read the full paper here. Authors: Sudheendra Raghav Neela, Jonas Juffinger, Lukas Maar, Daniel Gruss Artifacts: Github Repository, Zenodo Record (Available, Functional, and Reproducible) CVE-2025-21691: Announcement, Red Hat, NVD NIST, Debian Tracker, Suse. Introduction An operating system deals with pages, the smallest region of memory in a system using virtual memory1.

Hi everyone! I’m happy to share that my first first-author paper has been accepted to a conference recently about side-channel attacks on the Linux page cache.

Side-channel attacks on the page cache (first shown in 2019 by my PhD advisor et al.) were thought to have been mitigated since 2019 or thought to be impractical for a long time. Work that I (+my co-authors) did over the past year showed that such attacks were very possible, but also way more severe than initially thought.

It started out with me randomly encountering the cachestat syscall, introduced in kernel 6.5 (2022) to query the state of OS pages in the page cache. After a bit of investigation, we found that it leaks whether pages are in the page cache, including of globally-readable files not owned by that user.

I have a few examples of what attacks are possible on the linked blog post, but the tl;dr is you can detect whether binaries are run (like pkexec, which is the GUI that pops up for password prompts), infer which websites a different local-user visits on Firefox (via the libxul shared library), infer user and system behavior across docker containers, and a few more.

We also found a few more interesting stuff, like the posix_fadvise syscall with the POSIX_FADV_DONTNEED can deterministically remove pages from cache. The other fine grained details are available in the paper: https://snee.la/pdf/pubs/eviction-notice.pdf, but a general write up is in the blog post.

The cachestat vulnerability was assigned CVE-2025-21691 and was fixed by Linus Torvalds himself (first time interacting with him!)

Since I know Lemmy loves Linux (as much as I do, or even more), I thought I’d share it here :D. Feel free to ask any questions if you have any!

There’s also a Github repository of our code which has been peer-reviewed to be reproducible here: https://github.com/isec-tugraz/Eviction-Notice

  • DibbleDabble@lemmy.ml
    2·
    8 hours ago

    I’m already thinking about how to replicate that blue arrow in Fig. 2. It looks very clean. And the patterns in the plots do have a pgfplots vibe to it, so that makes sense.

    In case you’re not aware, it is also possible to have pgf outputs that preserve scaling with matplotlib with similar serif fonts for the labels that you can specify in matplotlibrc of the project. Hopefully you’d find that useful if you ever decide to use matplotlib beyond some quick plots.

    • A Basil Plant@lemmy.worldOP
      2·
      8 hours ago

      I could give you the tikz source of Fig 2 if you’d like. The patterns and colors of the plots took me almost a day to choose. I wanted to go for a color-blind friendly pallette and keep it looking still snazzy. (https://github.com/simon-pfahler/colorblind)

      I’m familiar with matplotlib -> PGFplots (using the Python tikzplotlib library). Unfortunately, I’ve decided against using it for the paper as it produces quite unmanageable outputs. Especially if I rerun experiments + with new data, and later want to change patterns, colors… It was always more of a hassle. I used it for my Master’s thesis.

      Instead, Python program -> show plot -> if okay, generate CSV.

      In LaTeX, have PGFplot code which reads CSV file and generates the data that way. Much, much easier to maintain.

      • DibbleDabble@lemmy.ml
        2·
        7 hours ago

        That colourblind palette is golden, thank you for sharing it. And I was just talking about me wanting have a crack at creating that arrow myself, but thank you for offering to share. I’ll be sure to reach out if I find myself being unable to replicate it.

        I wasn’t even talking about tikzplotlib. It’s just that pgf backend is now supported by matplotlib and you can produce pgf files with:

        import matplotlib.pyplot as plt
import matplotlib

matplotlib.use('pgf')

fig, ax = plt.subplots()
# Code related to plotting here

fig.savefig("outputfile.pgf")

        with relevant rcParams options in matplotlibrc, then import the pgf with:

        \begin{figure}[h]
    \centering
      \resizebox{\linewidth}{!}{
        \input{outputfile.pgf}
      }
    \caption{Caption here.}
\end{figure}

        But Python -> CSV -> LaTeX/pgf pipeline is quite smooth, for sure. I understand why you’d decide to opt for it without involving too many third-party dependencies.

        • A Basil Plant@lemmy.worldOP
          1·
          7 hours ago

          I’ll be sure to reach out if I find myself being unable to replicate it.

          No worries, and good luck! My email can be found on my website if you want it :D

          I wasn’t even talking about tikzplotlib. It’s just that pgf backend is now supported by matplotlib and you can produce pgf files with.

          Ah… I’ve think I’ve heard of it, but I never really registered that. Thanks for the info :D