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layout: post | ||
title: "Avoiding stack overflows on CHERIoT" | ||
date: 2024-05-01 | ||
categories: rtos stack programming | ||
author: "David Chisnall" | ||
--- | ||
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If you put code in a compartment and do nothing to protect the interfaces, there are a lot of ways that a caller can make that compartment crash. | ||
In some cases, this doesn't matter. | ||
The compartment exists to provide confidentiality and integrity, but not necessarily availability. | ||
The TLS compartment in the network stack is a good example of this. | ||
It provides strong flow isolation and so making it crash will impact only the TLS session of the caller. | ||
The caller can also simply call the close function on a TLS session and so we don't worry about their ability to break a TLS session, only about their ability to send plain text over the network or extract keying material from the TLS session. | ||
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In other contexts, availability is far more important. | ||
In the core of the RTOS, the scheduler and allocator both have availability requirements. | ||
If you can crash the allocator while it holds the lock over the heap, you can prevent any future memory allocation. | ||
If you can crash the scheduler in the middle of updating run queues, you may be able to prevent certain threads ever running. | ||
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In most platforms, it's easy to make a function crash by moving the stack pointer to near the end just before calling it. | ||
The function will run off the end of the stack and hit a guard page on MMU / MPU systems or the end of the stack capability on CHERI systems. | ||
This is even more crucial on embedded systems, where stacks tend to be small. | ||
Large desktop or server systems often have stacks of 1-4 MiBs, which are large enough for most programs to treat as infinite. | ||
Embedded systems may have stacks that are under 1 KiB. | ||
Even without the security implications from distrust between compartments, having systems fail because they ran out of stack space is far from ideal. | ||
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These problems are relevant on CHERIoT. | ||
The caller can constrain the amount of space available on the stack before a cross-compartment call. | ||
If the callee requires more stack space than the caller provides then this can cause problems. | ||
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From the start, the CHERIoT ABI has provided some mitigation for this. | ||
Every cross-compartment entry point is described by an entry in an export table. | ||
One of the fields in an export-table entry indicates the amount of stack space that a call requires. | ||
If the stack has less space than is available then the call will fail without invoking the callee at all. | ||
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This leads to an obvious problem: How do you set this value to something sensible? | ||
By default, the compiler sets it to the stack space required for the function that implements the entry point. | ||
This means that any function that doesn't call any other functions is fine. | ||
It also means that, if you put stack checks in the function *before* calling any other functions, then you can guarantee that they will work correctly. | ||
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This still leaves a lot of work to determine how much stack space you actually need. | ||
The compiler or other tooling could build a static control-flow graph for the current compilation unit, and possibly even the current compartment, but what happens if you call library functions? | ||
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It turns out that we already had the building block for a good solution. | ||
CHERIoT guarantees that you can't accidentally leak data left on the stack through a cross-compartment call. | ||
This is done by zeroing the portion of the stack that is going to be shared before and after a cross-compartment call. | ||
When we did this initially, we quickly realised that we were spending a lot of time zeroing memory that was already full of zeroes. | ||
This got worse the larger stacks were. | ||
If you had a 4 KiB stack and a function that used 128 bytes, you may still end up zeroing almost 4 KiB *twice* (once on call, once on return). | ||
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To fix this, we introduced the stack high-water mark. | ||
This is configured with the range of the stack and tracks all stores into that range. | ||
Any store below the current high-water mark (remember, stacks grow down, so the 'high'-water mark is actually at the bottom of the memory for the stack) moves the mark. | ||
The switcher can read this before and after the call and zero only memory that's used. | ||
If you start a thread, do some stack allocation, and then call a new compartment, we don't need to do any zeroing. | ||
If you call some internal functions, return, and then call another compartment, we zero only the bit of the stack that you've left data on. | ||
If you call a compartment that uses 128 bytes of stack space then we will zero 128 bytes of stack on return, independent of the stack size. | ||
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This means that we *already* had a mechanism for dynamically determining how much stack a particular compartment entry point needed. | ||
All that we needed to do was expose it. | ||
For C++, we've [wrapped this up in a class that lets you report the highest stack usage for a function across multiple invocations](https://cheriot.org/book/compartments.html#_ensuring_adequate_stack_space). | ||
A lot of functions have data-dependent control flow and so data-dependent worst-case stack usage. | ||
By running a set of tests over a function, you can find the worst-case stack usage. | ||
This class can either log the highest stack usage that it sees or can crash the compartment if the expected amount is exceeded. | ||
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Once you've made determined the maximum stack usage for a function, you can use the `__cheriot_minimum_stack` attribute to set the value in the export table. | ||
We've now done this for the allocator and the scheduler, which should make both robust. | ||
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Confidentiality and integrity were the primary goals for CHERIoT. | ||
Our first adversarial security evaluation did not find any ways of violating confidentiality or integrity. | ||
Since then, we've been working to add availability to the guarantees that we can provide. | ||
This is just one of many steps in making the CHERIoT platform a solid foundation for high-availability embedded systems. |