Gaining kernel code execution on an MTE-enabled Pixel 8
github.blog
github.blog
The problem with those GPUs in general is driver issues, the hardware is fine.
Yes, I'm talking about using cores like an ARM SMMU (which is an IO-MMU). Perhaps some GPUs do, but many (most?) don't including the Mali-G710 in this article that's currently shipping in the Pixel 8.
> The problem with those GPUs in general is driver issues, the hardware is fine.
Exactly. I want them to stop writing bespoke kernel code manually fiddling with some custom page table format that gives physical memory read/write primitives when they get it wrong.
See Qualcomm Adreno
VideoCore, IMG, Mali, the RDNA2 respun as "XClipse GPU" all do not use system standard IOMMUs to provide their user device contexts.
The rest of the article appears to be describing that a bug is actually caused by a race condition and use-after-free is simply a consequence of it.
EDIT: Ignore me, I was confusing that with the recent blog post they had about finding an issue with MTE applying to all system apps too. Looks like GrapheneOS should have this as of their 2024030600 release because it brings in the "full 2024-03-05 security patch level"
Sometimes they even adopt pre-release AOSP security patch levels or backport security fixes from unreleased AOSP or kernel sources.
The right kind of mitigations targets the 1st order primitive; the root cause of the bug.
Hardware solutions: CHERI (Morello, CheriIoT), MTE
Software mitigations: kalloc_type+dataPAC, AUTOSLAB, Firebloom, GuardedMemcpy, CastGuard, attack surface reduction
Safe programming languages: Rust, Swift
MTE/CHERI play pretty nicely - they help ensure that whatever bugs we have in these areas are killed at their root cause… MSR, MSRC and Azure Silicon pushed for… scaling CHERI down to RISC-V32E, the smallest core RISC-V specification.
Microsoft Research open-sourced a hardware/software stack for CHERI in IoT devices, https://msrc.microsoft.com/blog/2023/02/first-steps-in-cheri... CHERI-based microcontroller that aims to… get very strong security guarantees if we are willing to co-design the instruction set architecture (ISA), the application binary interface (ABI), isolation model, and the core parts of the software stack… our microcontroller achieves the following security properties:
Deterministic mitigation for spatial safety (using CHERI-ISA capabilities).
Deterministic mitigation for heap and cross-compartment stack temporal safety (using a load barrier, zeroing, revocation, and a one-bit information flow control scheme).
Fine-grained compartmentalization (using additional CHERI-ISA features and a tiny monitor).
David Chisnall, U of Cambridge, https://lobste.rs/s/gnjx2n/c_can_be_memory_safe#c_9ohzku via https://eclypsium.com/blog/a-faster-path-to-memory-safety-ch...> There are around 13 billion lines of open source C and C++, which end up in various TCBs. This number gets even bigger when you include proprietary code… if we all stopped writing C/C++ code now and every software engineer focused on rewriting legacy code in safe languages (and on the assumption that everything can be written in safe languages) then it would take 5-10 to replace everything and we’d likely see a lot of logic bugs because we’d be replacing old well-tested code with new code that would need different algorithms and data structures to fit with allowable idioms in safe languages.
> If we didn’t do the rewriting thing and just stopped writing code in C/C++, then at normal code replacement rates, our TCBs would be entirely safe in around 50 years. If we don’t all agree to stop writing C/C++, it’s at least 100 years.
> In contrast, if the major CPU vendors shipped CHERI CPUs in five years, most machines (and all high-value ones) would have memory safety within 15 years of today, without needing programmers to change their behaviour.
The first is the Sonata system: https://github.com/lowRISC/sonata-system. This comprises a dedicated PCB with an FPGA along with various peripherals and headers. The PCB design is done and will be available through Mouser (plus it's open source including the board layout so you can assemble your own if you like). We're currently working on the RTL for the FPGA. When complete you'll have a complete CHERIoT based microcontroller like system with documentation and tooling.
Additionally we're building the Symphony system, which combines Sonata with the OpenTitan Earl Grey root of trust: https://github.com/lowRISC/symphony-system
The exploit can probably be written in most languages, including Rust.
Anyway, the last time I looked into it, CHERI wasn't sound: It was still possible to write memory bugs on top of it. Have they fixed that yet?
Lifetime safety is a much harder problem to solve. Despite CHERI providing ""more robust"" bounds safety, the fact that you get decent lifetime safety for essentially free from MTE is a huge plus. The two technologies aren't incompatible so in theory you could bolt the two together to get MTE lifetime safety and CHERI bounds safety, but that would likely waste a ton of memory.
If we're talking years, that seems wildly optimistic. I imagine the bike-shedding alone would take that long.
Does anyone know what their "business reason" for doing research like this is? (not that a business reason should be needed, but like I said, I'm a bit surprised to see it here)
Man Yue Mo is a security researcher who finds some of the most complex and impactful bugs in the industry like crbug.com/40065473
Although, it wouldn’t be abnormal for a security team to have free time, and dedicate it to researching an emerging technology whether it directly contributes to the business goals or not. Of course I’m not talking about a security team that is reading log files from their SIEM while sitting in a SOC.
Semmle built CodeQL, now offered by GitHub (https://docs.github.com/en/code-security/code-scanning/intro...), which GitHub and Microsoft (see https://www.microsoft.com/en-us/security/blog/2023/11/02/ann...) want to associate with "deep security insight".
So they continue to fund this kind of novel security research, for which security practitioners across industry are grateful.
I think it's basically basic research [0]. In first order reasoning, github, as a product doesn't really need android security experts. But employing them has some potential long-term benefits.
I’ll paste:
Why does GitHub Security Lab do research like @mmolgtm’s recent work on bypassing MTE on the Pixel 8? This question was asked on Hacker News and we think it’s worth a short thread. news.ycombinator.com/item?id=397522…
First an important point: we only research open source code, which means that many parts of your phone (for example most of your apps) are out-of-scope for us. That said, all open source code is in-scope, including projects that aren’t hosted on GitHub. (Quote tweet reply to this tweet [2])
In this particular case, @mmolgtm found a bug in Arm Mali, which is an open source GPU driver used on many Android phones. Android itself is open source. https://developer.arm.com/downloads/-/mali-drivers/valhall-k...
Open source software is the foundation of much of the world’s software. So when open source wins, we win. And that’s why @GitHub takes its responsibility seriously, to help make open source software more secure.
GitHub Security Lab sits within @GitHubSecurity, and we focus exclusively on open source security with four main priorities:
First, we run the GitHub Advisory Database, which is a comprehensive database of open source vulnerabilities. https://t.co/U4HlXO2l1G
Second, we share information around secure coding practices, through blogs and video content. https://t.co/EdO5SZtR0B
Third, we use GitHub’s CodeQL to scan thousands of open source repositories for common security mistakes, like SQL injections or path traversals. https://t.co/m72rt2a5RL
And fourth, we do deep research on critical open source projects. @mmolgtm’s recent work on Arm Mail is an example of this. https://t.co/jxVYeoJjtO
The work that we do feeds into GitHub’s security products. For example, the advisory database is used to generate Dependabot alerts. https://docs.github.com/en/code-security/dependabot/dependab...
Similarly, our work with CodeQL provides feedback to the code scanning team to help improve and further develop the feature so that more vulnerabilities are caught quickly and automatically. https://docs.github.com/en/code-security/code-scanning/intro...
And these activities also benefit open source, because GitHub security products, including Dependabot and CodeQL, are free for open source projects!
Our deep research work is primarily intended to inspire the community, so that we can improve open source security together. That’s why we publish detailed blog posts and proof-of-concept exploits.
https://github.com/github/securitylab/tree/main/SecurityExpl...
We’re big believers in Linus's law: “given enough eyeballs, all bugs are shallow”. Together, we’re making open source software secure. https://en.wikipedia.org/wiki/Linus%27s_law
There are dozens of UI effects which rely on the GPU, and there's just no such thing as a 2D GPU these days, it makes no sense unless you're building a retro console or something.
So don't do that exact effect? This is a pretty weak objection.
> there's just no such thing as a 2D GPU these days, it makes no sense
This might be stronger but I'm not an expert on pixel pushing.
It looks less nice and is limited in some ways, but for business needs to does the job perfectly.