VulnHeap by r1chard-lyu

Description

The VulnHeap project is dedicated to the in-depth analysis and exploitation of vulnerabilities within heap memory management. It focuses on understanding the intricate workflow of heap allocation, chunk structures, and bin management, which are essential to identifying and mitigating security risks.

Goals

• Familiarize with heap
  • Heap workflow
  • Chunk and bin structure
  • Vulnerabilities
• Vulnerability
  • Use after free (UAF)
  • Heap overflow
  • Double free
• Use Docker to create a vulnerable environment and apply techniques to exploit it

Resources

• https://heap-exploitation.dhavalkapil.com/divingintoglibc_heap
• https://raw.githubusercontent.com/cloudburst/libheap/master/heap.png
• https://github.com/shellphish/how2heap?tab=readme-ov-file

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Contributing to Linux Kernel security by pperego

Description

A couple of weeks ago, I found this blog post by Gustavo Silva, a Linux Kernel contributor.

I always strived to start again into hacking the Linux Kernel, so I asked Coverity scan dashboard access and I want to contribute to Linux Kernel by fixing some minor issues.

I want also to create a Linux Kernel fuzzing lab using qemu and syzkaller

Goals

1. Fix at least 2 security bugs
2. Create the fuzzing lab and having it running

The story so far

• Day 1: setting up a virtual machine for kernel development using Tumbleweed. Reading a lot of documentation, taking confidence with Coverity dashboard and with procedures to submit a kernel patch
• Day 2: I read really a lot of documentation and I triaged some findings on Coverity SAST dashboard. I have to confirm that SAST tool are great false positives generator, even for low hanging fruits.
• Day 3: Working on trivial changes after I read this blog post: https://www.toblux.com/posts/2024/02/linux-kernel-patches.html. I have to take confidence with the patch preparation and submit process yet.
  • First trivial patch sent: using strtruefalse() macro instead of hard-coded strings in a staging driver for a lcd display
  • Fix for a dereference before null check issue discovered by Coverity (CID 1601566) https://scan7.scan.coverity.com/#/project-view/52110/11354?selectedIssue=1601566
• Day 4: Triaging more issues found by Coverity.
  • The patch for CID 1601566 was refused. The check against the NULL pointer was pointless so I prepared a version 2 of the patch removing the check.
  • Fixed another dereference before NULL check in iwlmvmparsewowlaninfo_notif() routine (CID 1601547). This one was already submitted by another kernel hacker :(
• Day 5: Wrapping up. I had to do some minor rework on patch for CID 1601566. I found a stalker bothering me in private emails and people I interacted with me, advised he is a well known bothering person. Markus Elfring for the record.

• Wrapping up: being back doing kernel hacking is amazing and I don't want to stop it. My battery pack is completely drained but changing the scope gave me a great twist and I really want to feel this energy not doing a single task for months.

  I failed in setting up a fuzzing lab but I was too optimistic for the patch submission process.

The patches

1

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toptop - a top clone written in Go by dshah

Description

toptop is a clone of Linux's top CLI tool, but written in Go.

Goals

Learn more about Go (mainly bubbletea) and Linux

Resources

GitHub

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Explore simple and distro indipendent declarative Linux starting on Tumbleweed or Arch Linux by janvhs

Description

Inspired by mkosi the idea is to experiment with a declarative approach of defining Linux systems. A lot of tools already make it possible to manage the systems infrastructure by using description files, rather than manual invocation. An example for this are systemd presets for managing enabled services or the /etc/fstab file for describing how partitions should be mounted.

If we would take inspiration from openSUSE MicroOS and their handling of the /etc/ directory, we could theoretically use systemd-sysupdate to swap out the /usr/ partition and create an A/B boot scheme, where the /usr/ partition is always freshly built according to a central system description. In the best case it would be possible to still utilise snapshots, but an A/B root scheme would be sufficient for the beginning. This way you could get the benefit of NixOS's declarative system definition, but still use the distros package repositories and don't have to deal with the overhead of Flakes or the Nix language.

Goals

• A simple and understandable system
• Check fitness of mkosi or write a simple extensible image builder tool for it
• Create a declarative system specification
• Create a system with swappable /usr/ partition
• Create an A/B root scheme
• Swap to the new system without reboot (kexec?)

Resources

• Ideas that have been floating around in my head for a while
• https://0pointer.net/blog/fitting-everything-together.html
• GNOME OS
• MicroOS
• systemd mkosi
• Vanilla OS

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Testing and adding GNU/Linux distributions on Uyuni by juliogonzalezgil

Join the Gitter channel! https://gitter.im/uyuni-project/hackweek

Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines. It also manages configuration, can run audits, build image containers, monitor and much more!

Currently there are a few distributions that are completely untested on Uyuni or SUSE Manager (AFAIK) or just not tested since a long time, and could be interesting knowing how hard would be working with them and, if possible, fix whatever is broken.

For newcomers, the easiest distributions are those based on DEB or RPM packages. Distributions with other package formats are doable, but will require adapting the Python and Java code to be able to sync and analyze such packages (and if salt does not support those packages, it will need changes as well). So if you want a distribution with other packages, make sure you are comfortable handling such changes.

No developer experience? No worries! We had non-developers contributors in the past, and we are ready to help as long as you are willing to learn. If you don't want to code at all, you can also help us preparing the documentation after someone else has the initial code ready, or you could also help with testing :-)

The idea is testing Salt and Salt-ssh clients, but NOT traditional clients, which are deprecated.

To consider that a distribution has basic support, we should cover at least (points 3-6 are to be tested for both salt minions and salt ssh minions):

1. Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
2. Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
3. Package management (install, remove, update...)
4. Patching
5. Applying any basic salt state (including a formula)
6. Salt remote commands
7. Bonus point: Java part for product identification, and monitoring enablement
8. Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
9. Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
10. Bonus point: testsuite enablement (https://github.com/uyuni-project/uyuni/tree/master/testsuite)

If something is breaking: we can try to fix it, but the main idea is research how supported it is right now. Beyond that it's up to each project member how much to hack :-)

• If you don't have knowledge about some of the steps: ask the team
• If you still don't know what to do: switch to another distribution and keep testing.

This card is for EVERYONE, not just developers. Seriously! We had people from other teams helping that were not developers, and added support for Debian and new SUSE Linux Enterprise and openSUSE Leap versions :-)

Pending

FUSS

FUSS is a complete GNU/Linux solution (server, client and desktop/standalone) based on Debian for managing an educational network.

https://fuss.bz.it/

Seems to be a Debian 12 derivative, so adding it could be quite easy.

• [W] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
• [W] Onboarding (salt minion from UI, salt minion from bootstrap script, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator) --> Working for all 3 options (salt minion UI, salt minion bootstrap script and salt-ssh minion from the UI).
• [W] Package management (install, remove, update...) --> Installing a new package works, needs to test the rest.
• [I] Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already). No patches detected. Do we support patches for Debian at all?
• [W] Applying any basic salt state (including a formula)
• [W] Salt remote commands
• [ ] Bonus point: Java part for product identification, and monitoring enablement

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FamilyTrip Planner: A Personalized Travel Planning Platform for Families by pherranz

Description

FamilyTrip Planner is an innovative travel planning application designed to optimize travel experiences for families with children. By integrating APIs for flights, accommodations, and local activities, the app generates complete itineraries tailored to each family’s unique interests and needs. Recommendations are based on customizable parameters such as destination, trip duration, children’s ages, and personal preferences. FamilyTrip Planner not only simplifies the travel planning process but also offers a comprehensive, personalized experience for families.

Goals

This project aims to: - Create a user-friendly platform that assists families in planning complete trips, from flight and accommodation options to recommended family-friendly activities. - Provide intelligent, personalized travel itineraries using artificial intelligence to enhance travel enjoyment and minimize time and cost. - Serve as an educational project for exploring Go programming and artificial intelligence, with the goal of building proficiency in both.

Resources

To develop FamilyTrip Planner, the project will leverage: - APIs such as Skyscanner, Google Places, and TripAdvisor to source real-time information on flights, accommodations, and activities. - Go programming language to manage data integration, API connections, and backend development. - Basic machine learning libraries to implement AI-driven itinerary suggestions tailored to family needs and preferences.

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Add a machine-readable output to dmidecode by jdelvare

Description

There have been repeated requests for a machine-friendly dmidecode output over the last decade. During Hack Week 19, 5 years ago, I prepared the code to support alternative output formats, but didn't have the time to go further. Last year, Jiri Hnidek from Red Hat Linux posted a proof-of-concept implementation to add JSON output support. This is a fairly large pull request which needs to be carefully reviewed and tested.

Goals

Review Jiri's work and provide constructive feedback. Merge the code if acceptable. Evaluate the costs and benefits of using a library such as json-c.

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FizzBuzz OS by mssola

Project Description

FizzBuzz OS (or just fbos) is an idea I've had in order to better grasp the fundamentals of the low level of a RISC-V machine. In practice, I'd like to build a small Operating System kernel that is able to launch three processes: one that simply prints "Fizz", another that prints "Buzz", and the third which prints "FizzBuzz". These processes are unaware of each other and it's up to the kernel to schedule them by using the timer interrupts as given on openSBI (fizz on % 3 seconds, buzz on % 5 seconds, and fizzbuzz on % 15 seconds).

This kernel provides just one system call, write, which allows any program to pass the string to be written into stdout.

This project is free software and you can find it here.

Goal for this Hackweek

• Better understand the RISC-V SBI interface.
• Better understand RISC-V in privileged mode.
• Have fun.

Resources

• SBI v2.0 ratified specification
• Blog post on SBI
• mssola/fbos

Results

The project was a resounding success Lots of learning, and the initial target was met.

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FastFileCheck work by pstivanin

Description

FastFileCheck is a high-performance, multithreaded file integrity checker for Linux. Designed for speed and efficiency, it utilizes parallel processing and a lightweight database to quickly hash and verify large volumes of files, ensuring their integrity over time.

https://github.com/paolostivanin/FastFileCheck

Goals

• Release v1.0.0

Design overwiew:

• Main thread (producer): traverses directories and feeds the queue (one thread is more than enough for most use cases)
• Dedicated consumer thread: manages queue and distributes work to threadpool
• Worker threads: compute hashes in parallel

This separation of concerns is efficient because:

• Directory traversal is I/O bound and works well in a single thread
• Queue management is centralized, preventing race conditions
• Hash computation is CPU-intensive and properly parallelized

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ESETv2 Emulator / interpreter by m.crivellari

Description

ESETv2 is an intriguing challenge developed by ESET, available on their website under the "Challenge" menu. The challenge involves an "assembly-like" language and a Python compiler that generates .evm binary files.

This is an example using one of their samples (it prints N Fibonacci numbers):

.dataSize 0
.code

loadConst 0, r1 # first
loadConst 1, r2 # second

loadConst 1, r14 # loop helper

consoleRead r3

loop:
    jumpEqual end, r3, r15

    add r1, r2, r4
    mov r2, r1
    mov r4, r2

    consoleWrite r1

    sub r3, r14, r3
    jump loop
end:
hlt

This language also supports multi-threading. It includes instructions such as createThread to start a new thread, joinThread to wait until a thread completes, and lock/unlock to facilitate synchronization between threads.

Goals

• create a full interpreter able to run all the available samples provided by ESET.
• improve / optimize memory (eg. using bitfields where needed as well as avoid unnecessary memory allocations)

Resources

• Challenge URL: https://join.eset.com/en/challenges/core-software-engineer
• My github project: https://github.com/DispatchCode/eset_vm2 (not 100% complete)

Achivements

Project still not complete. Added lock / unlock instruction implementation but further debug is needed; there is a bug somewhere. Actually the code it works for almost all the examples in the samples folder. 1 of them is not yet runnable (due to a missing "write" opcode implementation), another will cause the bug to show up; still not investigated, anyhow.

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Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov

Project Description

Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.

In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.

Continue with implementation of the missing features and improve the existing implementation:

• authentication (need to decide how it should be/or not related to salt auth)

• web service providing the control of states deployment

Goal for this Hackweek

• Implement missing key features

• Implement the tool for state deployment control with CLI

Resources

https://github.com/openSUSE/saline

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ClusterOps - Easily install and manage your personal kubernetes cluster by andreabenini

Description

ClusterOps is a Kubernetes installer and operator designed to streamline the initial configuration and ongoing maintenance of kubernetes clusters. The focus of this project is primarily on personal or local installations. However, the goal is to expand its use to encompass all installations of Kubernetes for local development purposes.
It simplifies cluster management by automating tasks and providing just one user-friendly YAML-based configuration config.yml.

Overview

• Simplified Configuration: Define your desired cluster state in a simple YAML file, and ClusterOps will handle the rest.
• Automated Setup: Automates initial cluster configuration, including network settings, storage provisioning, special requirements (for example GPUs) and essential components installation.
• Ongoing Maintenance: Performs routine maintenance tasks such as upgrades, security updates, and resource monitoring.
• Extensibility: Easily extend functionality with custom plugins and configurations.
• Self-Healing: Detects and recovers from common cluster issues, ensuring stability, idempotence and reliability. Same operation can be performed multiple times without changing the result.
• Discreet: It works only on what it knows, if you are manually configuring parts of your kubernetes and this configuration does not interfere with it you can happily continue to work on several parts and use this tool only for what is needed.

Features

• distribution and engine independence. Install your favorite kubernetes engine with your package manager, execute one script and you'll have a complete working environment at your disposal.
  
• Basic config approach. One single config.yml file with configuration requirements (add/remove features): human readable, plain and simple. All fancy configs managed automatically (ingress, balancers, services, proxy, ...).
• Local Builtin ContainerHub. The default installation provides a fully configured ContainerHub available locally along with the kubernetes installation. This configuration allows the user to build, upload and deploy custom container images as they were provided from external sources. Internet public sources are still available but local development can be kept in this localhost server. Builtin ClusterOps operator will be fetched from this ContainerHub registry too.
• Kubernetes official dashboard installed as a plugin, others planned too (k9s for example).
• Kubevirt plugin installed and properly configured. Unleash the power of classic virtualization (KVM+QEMU) on top of Kubernetes and manage your entire system from there, libvirtd and virsh libs are required.
• One operator to rule them all. The installation script configures your machine automatically during installation and adds one kubernetes operator to manage your local cluster. From there the operator takes care of the cluster on your behalf.
• Clean installation and removal. Just test it, when you are done just use the same program to uninstall everything without leaving configs (or pods) behind.

Planned features (Wishlist / TODOs)

• Containerized Data Importer (CDI). Persistent storage management add-on for Kubernetes to provide a declarative way of building and importing Virtual Machine Disks on PVCs for

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SUSE AI Meets the Game Board by moio

Use tabletopgames.ai’s open source TAG and PyTAG frameworks to apply Statistical Forward Planning and Deep Reinforcement Learning to two board games of our own design. On an all-green, all-open source, all-AWS stack!

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Results: Infrastructure Achievements

We successfully built and automated a containerized stack to support our AI experiments. This included:

• a Fully-Automated, One-Command, GPU-accelerated Kubernetes setup: we created an OpenTofu based script, tofu-tag, to deploy SUSE's RKE2 Kubernetes running on CUDA-enabled nodes in AWS, powered by openSUSE with GPU drivers and gpu-operator
• Containerization of the TAG and PyTAG frameworks: TAG (Tabletop AI Games) and PyTAG were patched for seamless deployment in containerized environments. We automated the container image creation process with GitHub Actions. Our forks (PRs upstream upcoming):
  • https://github.com/moio/TabletopGames/tree/hackweek24
  • https://github.com/moio/PyTAG/tree/hackweek24

./deploy.sh and voilà - Kubernetes running PyTAG (k9s, above) with GPU acceleration (nvtop, below)

Results: Game Design Insights

Our project focused on modeling and analyzing two card games of our own design within the TAG framework:

• Game Modeling: We implemented models for Dario's "Bamboo" and Silvio's "Totoro" and "R3" games, enabling AI agents to play thousands of games ...in minutes!
• AI-driven optimization: By analyzing statistical data on moves, strategies, and outcomes, we iteratively tweaked the game mechanics and rules to achieve better balance and player engagement.
• Advanced analytics: Leveraging AI agents with Monte Carlo Tree Search (MCTS) and random action selection, we compared performance metrics to identify optimal strategies and uncover opportunities for game refinement .
  • more about Bamboo on Dario's site
  • more about R3 on Silvio's site (italian, translation coming)
  • more about Totoro on Silvio's site

A family picture of our card games in progress. From the top: Bamboo, Totoro, R3

Results: Learning, Collaboration, and Innovation

Beyond technical accomplishments, the project showcased innovative approaches to coding, learning, and teamwork:

• "Trio programming" with AI assistance: Our "trio programming" approach—two developers and GitHub Copilot—was a standout success, especially in handling slightly-repetitive but not-quite-exactly-copypaste tasks. Java as a language tends to be verbose and we found it to be fitting particularly well.
• AI tools for reporting and documentation: We extensively used AI chatbots to streamline writing and reporting. (Including writing this report! ...but this note was added manually during edit!)
• GPU compute expertise: Overcoming challenges with CUDA drivers and cloud infrastructure deepened our understanding of GPU-accelerated workloads in the open-source ecosystem.
• Game design as a learning platform: By blending AI techniques with creative game design, we learned not only about AI strategies but also about making games fun, engaging, and balanced.

Last but not least we had a lot of fun! ...and this was definitely not a chatbot generated line!

The Context: AI + Board Games

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Run local LLMs with Ollama and explore possible integrations with Uyuni by PSuarezHernandez

Description

Using Ollama you can easily run different LLM models in your local computer. This project is about exploring Ollama, testing different LLMs and try to fine tune them. Also, explore potential ways of integration with Uyuni.

Goals

• Explore Ollama
• Test different models
• Fine tuning
• Explore possible integration in Uyuni

Resources

• https://ollama.com/
• https://huggingface.co/
• https://apeatling.com/articles/part-2-building-your-training-data-for-fine-tuning/

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Symbol Relations by hli

Description

There are tools to build function call graphs based on parsing source code, for example, cscope.

This project aims to achieve a similar goal by directly parsing the disasembly (i.e. objdump) of a compiled binary. The assembly code is what the CPU sees, therefore more "direct". This may be useful in certain scenarios, such as gdb/crash debugging.

Detailed description and Demos can be found in the README file:

Supports x86 for now (because my customers only use x86 machines), but support for other architectures can be added easily.

Tested with python3.6

Goals

Any comments are welcome.

Resources

https://github.com/lhb-cafe/SymbolRelations

symrellib.py: mplements the symbol relation graph and the disassembly parser

symrel_tracer*.py: implements tracing (-t option)

symrel.py: "cli parser"

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