Is RAM wiped before use in another LXC container?
security.stackexchange.com
security.stackexchange.com
A running container is just a process that is using certain kernel features: cgroup, namespaces, pivotroot.
LXC has a different DX around containers than OCI containers do, but the same rules apply.
Docker/ OCI containers tend to be a single process and LXC containers have a collection of processes.
But in either case they are just processes running on the host in a different namespace.
So they feel different to use, but use the same building blocks (to my understanding).
The people working with Docker, even if they are developers doing development work, are still users of Docker, aren't they? I mean, the GUI of an IDE is still part of its UX, right? Even though it's for developers doing development work?
It's possible you are right but I'm not an expert. I always think of the developer experience is the experience of developers using the tools and APIs you produce.
The program continues to run to allow you to load in shell code that'll be run by the kernel.
Your task is basically to write some shellcode to scan the memory for the flag. So now I know that at least some Linux-es don't clean up after a process exits, and you can get the contents of memory when you have kernel privileges. This is not so easy if you're scanning memory as root since /dev/mem or whatever won't reveal that process memory.
edit: apparently the runtime option is called `init_on_alloc` and the compile-time option (which determines the default of the runtime option) is called `CONFIG_INIT_ON_FREE_DEFAULT_ON`.
• init_on_alloc (default set by CONFIG_INIT_ON_ALLOC_DEFAULT_ON)
• init_on_free (default set by CONFIG_INIT_ON_FREE_DEFAULT_ON)
I wish there were flags similar to this for the GPU memory. Even something that zero's GPU memory on reboot would be nice. I can always see the previous desktop after a reboot for a brief moment.
[1] - https://patchwork.kernel.org/project/linux-mm/patch/20190617...
In the normal configuration:
Is it not zeroed if the memory is assigned to the same process???
Is it zeroed when the system is idle???
Is it zeroed in batches that are more memory friendly???
Memory pages freed from userspace might be reused in kernelspace.
If, for instance, the memory is re-used in the kernel's page cache, then the kernel doesn't need to zero it out before copying the to-be-cached data into the page.
Edit: I seem to remember back in the 1990s that the kernel at least in some cases wouldn't zero-out pages previously used by the kernel before giving them to userspace, sometimes resulting in kernel secrets being leaked to arbitrary userspace processes. Maybe I'm missremembering, and it was just leakage of secrets between userspace processes. In any case, in the 1990s, Linux was way too lax about leaking data from freed pages.
That's not relevant here; from the perspective of the kernel pages are either assigned to a process, or they're not. If an application fails to free memory correctly, that only means it'll keep having pages assigned to it that it no longer uses, but eventually those pages will always be released (by the kernel upon termination of the process, in the worst case).
e.g. if your code is doing
ptr = malloc()
memcpy(mydata, ptr)
More importantly, it's not safe. Another thread in the same process can see ptr between the malloc and the memcpy!
Edit: also, of course, malloc and memcpy are C runtime functions, not syscalls, so checking what happens after malloc() would require the kernel to have much more sophisticated analysis than just looking a few instructions ahead of the calling thread's %%eip/%%rip. While handling malloc()'s mmap() or brk() allocation, the kernel would need to be able to look one or two call frames up the call stack, past the metadata accounting that malloc is doing to keep track of the newly acquired memory, perhaps look at a few conditional branches, trace through the GOT and PLT entries to see where the memcpy call is actually going, and do so in a way that is robust to changes in the C runtime implementation. (Of course, in practice, most C compilers will inline a memcpy implementation, so in the common case, it wouldn't have to chase the GOT and PLT entries, but even then, it's way too complicated for the kernel to figure out if anything non-trivial is happening between mmap()/brk() and the memory being overwritten.)
Edit 2: To be robust in the completely general case, even if it were trivial to identify the inlined memcpy implementation, and it were clearly defined "something non-trivial happens", determining if "something non-trivial happens" between mmap()/brk() and memcyp() would involve solving the halting problem. (Imposssible in the general case.)
malloc() == 'reservation' (but not paged in!) memory
// If touched / updated THEN the memory's paged in
However, that wouldn't solve the problem of other threads in the same process being able to see the page before it's fully overwritten, or debugging processes, or using a signal handler to invisibly jump out of the initialization loop in the middle, etc. There are workarounds to all of these issues, but they all have performance and complexity costs.
If you want make sure it is zero you will want calloc. If you know you are going to copy something in on the next step like your example you probably can skip calloc and just us malloc. calloc is nice for when you are doing thigs like linked lists/trees/buffers and do not want to have steps to clean out the pointers or data.
- lots of code is written under the assumption that free is fast
- memory is zeroed in the background, unless memory pressure forces the kernel to zero when handing it out
yes mainly that,
and if the system isn't idle but also doesn't use all phys. memory it might not be zeroed for a very long time
> Is it not zeroed if the memory is assigned to the same process???
idk. what the current state of this is in linux but at least in the past for some systems for some use cases related to mapped memory this was the case
What could be interesting if there were a CPU instruction to tell the RAM to do it. Then you would avoid the memory bandwidth impact of freeing the memory. But I don’t think there’s any such instruction for the CPU/memory protocol even today. Not sure why.
And in some cases on some systems the DRM controller might zero the memory in some situations, in which cases you could say it was done by hardware.
Did you mean DMA controller? Or do you have more information?
But...wouldn't it be relatively trivial to have an instruction that tells the memory controller "set range from address y to x to 0" and let it handle it? Actually slamming a bunch of 0's out over the bus seems so very suboptimal.
Having the memory controller or memory module do it is complicated somewhat because it needs to be coherent with the caches, needs to obey translation, etc. If you have the memory controller do it, it doesn't save bandwidth. But, on the other hand, with a write back cache, your zeroing may never need to get stored to memory at all.
Further, if you have the module do it, the module/sdram state machine needs to get more complicated... and if you just have one module on the channel, then you don't benefit in bandwidth, either.
A DMA controller can be set up to do it... but in practice this is usually more expensive on big CPUs than just letting a CPU do it.
It's not really tying up a processor because of superscalar, hyperthreading, etc, either; modern processors have an abundance of resources and what slows things doing is things that must be done serially or resources that are most contended (like the bus to memory).
As I type this, I'm realizing how little I know about the protocol between the CPU and the memory modules--if anyone has an accessible link on the subject, I'd be grateful.
Also the question is what is this % in relation to?
Probably that freeing get up to 5% slower, which is reasonable given that before you often could use idle time to zero many of the pages or might not have zeroed some of the pages at all (as they where never reused).
https://travisdowns.github.io/blog/2020/05/13/intel-zero-opt...
Just trying to check my understanding of what the 3-5% delta is. Seems like a tiny tradeoff for any workstation (I wouldn't notice the difference at least). The tradeoff for servers might vary depending on what they are doing (shared versus owned, etc)
With exponentially increasing processor performance it does make sense for workstations where physical access should be considered in the threat model.
But then again, I run a few companies that deal with sensitive data. If I were just a gamer, I wouldn't care.
This flag puts an additional obstacle in the attacker's path. If you have private key material protecting valuable property, you definitely want to throw up as many roadblocks as possible.
[0] https://www.usenix.org/legacy/event/sec08/tech/full_papers/h...
Wouldn’t the memory need to bee free’d first for this to have any effect?
Though in my mind well written software should be zeroing the memory out before freeing if it held sensitive data.
1) abnormal program termination due to signals, memory pressure/oom killer, aborts in other threads serving different requests, and so on. These events could race with the memory zeroing.
2) bugs in the implementation where memory isn't zeroed in all paths
3) interactions between compiling, standard libraries, language runtimes and optimization passes causing memory zeroing to be skipped.
All these cases have happened time and time again in the wild. Hence having additional safety nets is useful.
These patches were endorsed by folks working on chromeos and Android security. I would suppose that they want them to put additional safeguards behind full disk encryption keys and may also be concerned with quality of implementation issues in 3rd party or vendor blobs.
A cold boot attack relies on a cold boot of the system to evade kernel protections(as opposed to a warm boot where the kernel can zero memory.)
The name has nothing to do with reducing the temperature of the ram to extend the time it takes bytes to vanish in ram.
> For those who think this is only theoretical: They were able to use this technique to create a bootable USB device which could determine someone's Truecrypt hard-drive encryption key automatically, just by plugging it in and restarting the computer. They were also able to recover the memory-contents 30 minutes+ later by freezing the ram (using a simple bottle of canned-air) and removing it. Using liquid nitrogen increased this time to hours.
For more details, see the paper Lest We Remember.
E.g. on a crypto key server. Less if it's a server which encrypts data en mass, but e.g. one which signs longer valid auth tokens or one which hold middle layer certificates which are once every few hours used to create a cert used to encrypt/sign data en mass used on a different server etc.
exactly, the only guarantee is that things are zeroed before handing them out to a different process, but there is some potential time gap between releasing memory back to the kernel and it being cleaned, a gap which can outlive the live of a process
> and you can get the contents of memory when you have kernel privileges. This is not so easy [..] as root
yes, root has much less privileges then the kernel, but often can gain kernel privileges.
But this is where e.g. lockdown mode comes in which denies the root users such privilege escalation (oversimplified, it's complicated). Main problem is that lockdown mode is not yet compatible with suspend to disk (hibernation), even through its documentation implies it is, if your have a encrypted hibernation. (This is misleading as it refers to a not yet existing feature where the kernel creates a encrypted image which is also tamper proof even if root tries to tamper. On the other hand suspend to an encrypted partition is possible in Linux, but not enough for lockdown mode to work.)
The TL;DR answer to the actual question is: processes generally don't get access to each other's memory unless there is some trust relation (like being the parent process, or being allowed to attach a debugger), and being in a container doesn't change that, the same restrictions apply and you always get zeroed-out memory from the kernel. It's when you use a different allocator that you might get nonzeroed memory from elsewhere in your own process (not a random other process).
Blame UNIX for that, and the fork() system call.
It's a design quirk. fork() duplicates the process. So suppose your web browser consumes 10GB RAM out of the 16GB total on the system, and wants to run a process for anything. Like it just wants to exec something tiny, like `uname`.
1. 10GB process does fork().
2. Instantly, you have two 10GB processes
3. A microsecond later, the child calls exec(), completely destroying its own state and replacing it with a 36K binary, freeing 10GB RAM.
So there's two ways to go there:
1. You could require step 2 to be a full copy. Which means either you need more RAM, a huge chunk of which would always sit idle, or you need a lot of swap, for the same purpose.
2. We could overlook the memory usage increase and pretend that we have enough memory, and only really panic if the second process truly needs its own 10GB RAM that we don't have. That's what Linux does.
The problem with #2 is that dealing with this happens completely in the background, at times completely unpredictable to the code. The OS allocates memory when the child changes memory, like does "a=1" somewhere. A program can't handle memory allocations failures there because as far as it knows, it's not allocating anything.
So what you get is this fragile fiction that sometimes breaks and requires the kernel to kill something to maintain the system in some sort of working state.
Windows doesn't have this issue at all because it has no fork(). New processes aren't children and start from scratch, so firefox never gets another 10GB sized clone. It just starts a new, 36K sized process.
No, that's not how it works. The process table gets duplicated and copy-on-write takes care of the pages. As long as they are identical they will be shared, there is no way that 10GB of RAM will be allocated to the forked process and that all of the data will be copied.
If kernel could not reserve memory for forked process, overcommit would not be necessary.
Only without overcommit does the kernel does need to start accounting for hypothetically-writable memory before it actually is written to.
What overcommit enables is more efficient use of memory for applications that request more memory than they use (which is most of them) and more efficient use of page cache. It also pretty much guarantees an app gets memory when it asks for it, at the cost of getting oom-killed later if the system as a whole runs out.
> 2. We could overlook the memory usage increase and pretend that we have enough memory, and only really panic if the second process truly needs its own 10GB RAM that we don't have. That's what Linux does
"pretend" → share the memory and hope most of it will be read-only or unallocated eventually; "truly needs to own" → CoW
Besides that the bulk of the fork calls are just a preamble to starting up another process and exiting the current one. It's mostly a hack to ensure continuity for stdin/stdout/stderr and some other resources.
What usually happens in practice is you're almost OOM, and one of the processes running in the system writes to a page shared with another process, forcing the system to start good ol' OOM killer.
Sorry, but no, it can't happen, you can not fork a process and end up with twice the memory requirements just because of the fork. What you can do is to simply allocate more memory than you were using before and keep writing.
The OOM killer is a nasty hack, it essentially moves the decision about what stays and what goes to a process that is making calls way above its pay grade, but overcommit and OOM go hand in hand.
3. A microsecond later, the child calls exec(), decrementing the reference count to the memory shared with the parent[1] and faulting in a 36k binary, bringing our new total memory usage to 1,045,612KB (1,048,576K + 36K)
CoW has existed since at least 1986, when CMU developed the Mach kernel.
What GP is really talking about is overcommit, which is a feature (on by default) in Linux which allows you to ask for more memory than you have. This was famously a departure from other Unixes at the time[2], a departure that fueled confusion and countless flame wars in the early Internet.
[1] https://unix.stackexchange.com/questions/469328/fork-and-cow... [2] https://groups.google.com/g/comp.unix.solaris/c/nLWKWW2ODZo/...
Today's RAM is cheap.
At least that design failure of UNIX has been fixed long ago. There are posix_spawn(3) and various clone(2) flavours which allow to spawn new process without copying the old one. And a lot of memory-intensive software actually use them, so modern Linux distros can be used without memory overprovisioning.
I'd rather blame people who are still using fork(2) for anything that can consume more than 100MB of memory.
Having this ridiculous setting as the default has basically ensured that we can never turn it off because developers expect things to work this way. They have no idea what to do if malloc errors on them. They like being able to make 1TB allocs without worrying about the consequences and just letting the kernel shoot processes in the head randomly when it all goes south. Hell, the last time this came up many swore that there was literally nothing a programmer could do in the event of OOM. Learned helplessness.
It's a goddamned mess and like many of Linux's goddamned messes not only are we still dealing with it in 2023, but every effort to do anything about it faces angry ranty backlash.
What makes the approach uniquely unsuitable for memory management? The entire idea of swapping goes out of the window without overprovisioning as well, for better or worse.
> What makes the approach uniquely unsuitable for memory management?
The fact that something like OOM killer even needs to exist. Killing random processes to free up memory you blindly promised but couldn't deliver is not a reasonable way to do things.
For example, it's a common pattern in many languages and frameworks to preload and fully initialize one worker process and then just fork that as often as required. The assumption there is that, while most of the memory is theoretically writable, practically, much of it is written exactly once and can then be shared across all workers. This both saves memory and the time needed to uselessly copy it for every worker instance (or alternatively to re-initialize the worker every single time, which can be costly if many of its data structures are dynamically computed and not just read from disk).
How do you do that without fork()/overprovisioning?
I'm also not sure whether "giving other examples" fits the bill of "whataboutism", as I'm not listing other examples of bad things to detract from a bad thing under discussion – I'm claiming that all of these things are (mostly) good and useful :)
You use threads. The part that fork() would have kept shared is still shared, the part that would have diverged is allocated inside each thread independently.
And if you find dealing with locking undesirable you can use some sort of message system, like Qt signals to minimize that.
That’s exactly my criticism of that approach: It’s conceptually trickier (fork is opt-in for sharing; threads are opt-out/require explicit copying) and requires duplicating all that memory, whether threads end up ever writing to it or not.
Threads have their merits, but so do subprocesses and fork(). Why force developers to use one over the other?
I used to agree with you, but fork() seems to have definitely been left behind. It has too many issues.
* fork() is slow. This automatically makes it troublesome for small background tasks.
* passing data is inconvenient. You have to futz around with signals, return codes, socketpair or shared memory. It's a pain to set up. Most of what you want to send is messages, but what UNIX gives you is streams.
* Managing it is annoying. You have to deal with signals, reaping, and doing a bunch of state housekeeping to keep track of what's what. A signal handler behaves like an annoying, really horribly designed thread.
* Stuff leaks across easily. A badly designed child can feed junk into your shared filehandles by some accident.
* It's awful for libraries. If a library wants to use fork() internally that'll easily conflict with your own usage.
* It's not portable. Using fork() automatically makes your stuff UNIX only, even if otherwise nothing stops it from working on Windows.
I think the library one is a big one -- we need concurrency more than ever, but under the fork model different parts of the code that are unaware of each other will step over each other's toes.
But what would be better? This way I can massage my data in one process, and then fork as many other processes that use this data as I like without having to serialise it to disk and and then load it again. If the data is not modified after fork it consumes much less memory (only the page tables). Usually a little is modified, consuming only a little memory extra. If all of it is modified it doesn't consume more memory than I would have otherwise (hopefully, not sure if the Linux implementation still keeps the pre-fork copy around).
(And no, not threads. They would share modifications, which I don't want. Also since I do this in python they would have terrible performance.)
Shared memory came much later than fork did.
As with all such stupid simple mechanisms, I would not advise its use if your program spans more than one .c file and more than a thousand lines.
Maybe there should be yet another flavor of fork() that does copy-on-write, but treats the memory as already-copied for physical memory accounting purposes? (Not sure if "copy-on-write but budget as distinct" is actually representable in Linux's or other Unixes' memory model, though.)
How about a version which copies the pages but marks them read-only in the child process, except for a set of ranges passed to fork (which would be copy-on-write as now). The child process then has to change any read-only pages to copy-on-write (or similar) to modify them.
This allows the OS to double-count and hence deny fork if the range of pages passed to fork leads to out of memory situation. It also allows the OS to deny the child process changing any read-only pages if it would lead to an out of memory situation. Both of those scenarios could be gracefully handled by the processes if they wish.
It would also keep the current positive behavior of the forked process having read access to the parent memory for data structures or similar.
> ... the behavior is undefined if the process created by vfork() either modifies any data other than a variable of type pid_t used to store the return value from vfork() ...
But the time between fork and exec is exactly where you do a lot of setup, like IO redirection, dropping privileges, setuid(), setting a signal mask (nohup) etc. and I don't think you can do that without setting any variables. You certainly write to the stack when calling a function.
If you can't do these things you can't really use it to implement posix_spawn(). I guess it could use vfork() in the case no actions are required, but only then.
(Obviously, that's the super-simplified version, and I don't fully understand the subtleties involved, but that's exactly what GP means: it's harder to analyse)
To make it slightly more complicated: you don't pay for the 10 GB directly, but you still pay for setting up the metadata, and that scales with the amount of virtual memory used.
I guess the case you want to highlight is more if you for example mmap() 10 GB of RAM on that 16 GB machine that only has 5 GB unused swap space left and where all of the physical RAM is filled with dirty pages already. Should the mmap() succeed, and then the process is killed if it eventually tries to use more pages than will fit in RAM or the backing swap? This is the overcommit option which is selectable on Linux. I think the defaults seem pretty good and accept that a process can get killed long after the "explicit" memory mapping call is done.
Given that most code I have seen would not be able to handle an allocation failure gracefully I wouldn't call it "blame", if the OS just silently failed memory allocations on whatever program tried to allocate next you would basically end up with a system where random applications crash, which is similar to what the OOM killer does, just with no attempt to be smart about it. Even better, it is outright impossible to gracefully handle allocation failures in some languages, see for example variable length arrays in C.
Also, why would you bother to handle it gracefully when the OS won't allow you to do it?
Also, outright impossible in some languages? Just don't use VLAs if then? "Problem" solved.
There are many situations where you can get an allocation failure even with over provisioning enabled.
> Just don't use VLAs if then? "Problem" solved.
Yes, just don't use that language feature that is visually identical to a normal array. Then make sure that your standard library implementation doesn't have random malloc calls hidden in functions that cannot communicate an error and abort instead https://www.thingsquare.com/blog/articles/rand-may-call-mall.... Then ensure that your dependencies follow the same standards of handling allocation failures ... .
I concede that it might be possible, but you are working against an ecosystem that is actively trying to sabotage you.
Yes, mallocs in standard library is a problem. But this is rather the result of a mindset where over provision exist than anything else.
Also, if you DO use fork() without immediately doing an exec(), and start writing all over your existing allocations... just don't?
What's really needed is io_uring_spawn but that's still a WIP. https://lwn.net/Articles/908268/
vfork followed immediately by exec gives you Windows-like process creation, and last I checked, despite having the overhead of a second syscall, was still faster than process creation on Windows.
Java has JSP, Java Server Pages. JSP processing translates a JSP file into Java source code, compiles it, then caches, loads, and executes the resulting class file.
Back then, the server would invoke the javac compiler through a standard fork and exec.
That’s all well and good, save when you have a large app server image sucking up the majority of the machine. As far as we could tell, it was a copy on write kind of process, it didn’t actually try to do the actual work when forking the app server. Rather it tried to do the allocation, found it didn’t have the space or swap, and just failed with a system OOM error (which differs from a Java out of memory/heap error).
As I recall adding swap was the short term fix (once we convinced the ops guy that, yes it was possible to “run out of memory”). Long term we made sure all of our JSPs were pre-compiled.
Later, this became a non issue for a variety of reasons, including being able to run the compiler natively within a running JVM.
https://youtu.be/YB6LTaGRQJg https://youtu.be/c_5Jy_AVDaM https://youtu.be/DpnXaNkM9_M
The code is in Rust but that doesn't matter for the explanation.
Generally browsers allocate large swaths of address space as guard pages (they're unmapped, but accesses into them will trap). Or they'll double map pages, so that the same physical page shows up multiple times in the virtual address space.
That’s a pretty big library to gloss over from a security or working programmer perspective!
(Corrections to perspective welcome.)
In the context of the question, I assume the asker was mostly interested in reading some kind of sensitive data from a previous process, not reading the same librsry-code-only memory or something.
Note: all of this could be wrong, it was just my understanding
Edit: looks like this answers that: https://stackoverflow.com/questions/20857134/memory-write-pr...
Replace and repeat with SQL, machine language, everything below modern programming languages.
zero memory on free (3-5% average system performance impact, due to touching cold memory)
init_on_free=1
init_on_alloc=1You can't just peek another process' GPU memory thru UMD app, either. Per-process virtual memory mechanisms similar to CPUs are also present in GPUs, which is the whole reason that resources are explicitly imported/exported across APIs via special API calls.
In theory you could have some sort of complex per-process scrambling system to avoid leaking information, but I think implementations actually just zero the memory.
GPU drivers on different operating systems can be more or less buggy; Windows and Linux generally seem to do the right thing, but MacOS is a bit more haphazard.
Of course that's for a trivial program. If you freed something, that probably wasn't returned to the OS, and the next malloc might just recycle it.
Your first request in your program, you'll get clean memory from the OS.