Changingos.urandom()on platforms with the getrandom() system call

This PEP proposes that in Python 3.6+,os.urandom()be updated to call thegetrandom()syscall in non-blocking mode if available and raise BlockingIOError:systemrandomnumbergeneratorisnotready;seesecrets.token_bytes() if the kernel reports that the call would block.

This behaviour will then propagate through to the existing random.SystemRandom,which provides a relatively thin wrapper around os.urandom()that matches therandom.Random()API.

However, the newsecretsmodule introduced byPEP 506will be updated to catch the new exception and implicitly wait for the system random number generator if the exception is ever encountered.

In all cases, as soon as a call to one of these security sensitive APIs succeeds, all future calls to these APIs in that process will succeed without blocking (once the operating system random number generator is ready after system boot, it remains ready).

On Linux and NetBSD, this will replace the previous behaviour of returning potentially predictable results read from/dev/urandom.

On FreeBSD, Solaris, and Illumos, this will replace the previous behaviour of implicitly blocking until the system random number generator is ready. However, it is not clear if these operating systems actually allow userspace code (and hence Python) to run before the system random number generator is ready.

Note that in all cases, if calling the underlyinggetrandom()API reports ENOSYSrather than returning a successful response or reportingEAGAIN, CPython will continue to fall back to reading from/dev/urandomdirectly.

Addingsecrets.wait_for_system_rng()

A new exception shouldn’t be added without a straightforward recommendation for how to resolve that error when encountered (however rare encountering the new error is expected to be in practice). For security sensitive code that actually does need to use the lower level interfaces to the system random number generator (rather than the newsecretsmodule), and does receive live bug reports indicating this is a real problem for the userbase of that particular application rather than a theoretical one, this PEP’s recommendation will be to add the following snippet (directly or indirectly) to the __main__module:

importsecrets
secrets.wait_for_system_rng()

Or, if compatibility with versions prior to Python 3.6 is needed:

try:
importsecrets
exceptImportError:
pass
else:
secrets.wait_for_system_rng()

Within thesecretsmodule itself, this will then be used in token_bytes()to block implicitly if the new exception is encountered:

deftoken_bytes(nbytes=None):
ifnbytesisNone:
nbytes=DEFAULT_ENTROPY
try:
result=os.urandom(nbytes)
exceptBlockingIOError:
wait_for_system_rng()
result=os.urandom(nbytes)
returnresult

Other parts of the module will then be updated to usetoken_bytes()as their basic random number generation building block, rather than calling os.urandom()directly.

Application frameworks covering use cases where access to the system random number generator is almost certain to be needed (e.g. web frameworks) may choose to incorporate a call tosecrets.wait_for_system_rng()implicitly into the commands that start the application such that existing calls to os.urandom()will be guaranteed to never raise the new exception when using those frameworks.

For cases where the error is encountered for an application which cannot be modified directly, then the following command can be used to wait for the system random number generator to initialize before starting that application:

Python 3-c"import secrets; secrets.wait_for_system_rng()"

For example, this snippet could be added to a shell script or a systemd ExecStartPrehook (and may prove useful in reliably waiting for the system random number generator to be ready, even if the subsequent command is not itself an application running under Python 3.6)

Given the changes proposed toos.urandom()above, and the inclusion of anos.getrandom()API on systems that support it, the suggested implementation of this function would be:

ifhasattr(os,"getrandom"):
# os.getrandom() always blocks waiting for the system RNG by default
defwait_for_system_rng():
"""Block waiting for system random number generator to be ready" ""
os.getrandom(1)
return
else:
# As far as we know, other platforms will never get BlockingIOError
# below but the implementation makes pessimistic assumptions
defwait_for_system_rng():
"""Block waiting for system random number generator to be ready" ""
# If the system RNG is already seeded, don't wait at all
try:
os.urandom(1)
return
exceptBlockingIOError:
pass
# Avoid the below busy loop if possible
try:
block_on_system_rng=open("/dev/random","rb")
exceptFileNotFoundError:
pass
else:
withblock_on_system_rng:
block_on_system_rng.read(1)
# Busy loop until the system RNG is ready
whileTrue:
try:
os.urandom(1)
break
exceptBlockingIOError:
# Only check once per millisecond
time.sleep(0.001)

On systems where it is possible to wait for the system RNG to be ready, this function will do so without a busy loop ifos.getrandom()is defined, os.urandom()itself implicitly blocks, or the/dev/randomdevice is available. If the system random number generator is ready, this call is guaranteed to never block, even if the system’s/dev/randomdevice uses a design that permits it to block intermittently during normal system operation.

Limitations on scope

No changes are proposed for Windows or Mac OS X systems, as neither of those platforms provides any mechanism to run Python code before the operating system random number generator has been initialized. Mac OS X goes so far as to kernel panic and abort the boot process if it can’t properly initialize the random number generator (although Apple’s restrictions on the supported hardware platforms make that exceedingly unlikely in practice).

Similarly, no changes are proposed for other *nix systems that do not offer thegetrandom()syscall. On these systems,os.urandom()will continue to block waiting for the system random number generator to be initialized.

While other *nix systems that offer a non-blocking API (other than getrandom()) for requesting random numbers suitable for use in security sensitive applications could potentially receive a similar update to the one proposed forgetrandom()in this PEP, such changes are out of scope for this particular proposal.

Python’s behaviour on older versions of affected platforms that do not offer the newgetrandom()syscall will also remain unchanged.

Ensuring thesecretsmodule implicitly blocks when needed

This is done to help encourage the meme that arises for folks that want the simplest possible answer to the right way to generate security sensitive random numbers to be “Use the secrets module when available or your application might crash unexpectedly”, rather than the more boilerplate heavy “Always call secrets.wait_for_system_rng() when available or your application might crash unexpectedly”.

It’s also done due to the BDFL having a higher tolerance for APIs that might block unexpectedly than he does for APIs that might throw an unexpected exception[11].

RaisingBlockingIOErrorinos.urandom()on Linux

For several years now, the security community’s guidance has been to use os.urandom()(or therandom.SystemRandom()wrapper) when implementing security sensitive operations in Python.

To help improve API discoverability and make it clearer that secrecy and simulation are not the same problem (even though they both involve random numbers),PEP 506collected several of the one line recipes based on the lower levelos.urandom()API into a newsecretsmodule.

However, this guidance has also come with a longstanding caveat: developers writing security sensitive software at least for Linux, and potentially for some other *BSD systems, may need to wait until the operating system’s random number generator is ready before relying on it for security sensitive operations. This generally only occurs ifos.urandom()is read very early in the system initialization process, or on systems with few sources of available entropy (e.g. some kinds of virtualized or embedded systems), but unfortunately the exact conditions that trigger this are difficult to predict, and when it occurs then there is no direct way for userspace to tell it has happened without querying operating system specific interfaces.

On *BSD systems (if the particular *BSD variant allows the problem to occur at all) and potentially also Solaris and Illumos, encountering this situation meansos.urandom()will either block waiting for the system random number generator to be ready (the associated symptom would be for the affected script to pause unexpectedly on the first call toos.urandom()) or else will behave the same way as it does on Linux.

On Linux, in Python versions up to and including Python 3.4, and in Python 3.5 maintenance versions following Python 3.5.2, there’s no clear indicator to developers that their software may not be working as expected when run early in the Linux boot process, or on hardware without good sources of entropy to seed the operating system’s random number generator: due to the behaviour of the underlying/dev/urandomdevice,os.urandom() on Linux returns a result either way, and it takes extensive statistical analysis to show that a security vulnerability exists.

By contrast, ifBlockingIOErroris raised in those situations, then developers using Python 3.6+ can easily choose their desired behaviour:

1. Wait for the system RNG at or before application startup (security sensitive)
2. Switch to using the random module (non-security sensitive)

Makingsecrets.wait_for_system_rng()public

Earlier versions of this PEP proposed a number of recipes for wrapping os.urandom()to make it suitable for use in security sensitive use cases.

Discussion of the proposal on the security-sig mailing list prompted the realization[9]that the core assumption driving the API design in this PEP was that choosing between letting the exception cause the application to fail, blocking waiting for the system RNG to be ready and switching to using the randommodule instead ofos.urandomis an application and use-case specific decision that should take into account application and use-case specific details.

There is no way for the interpreter runtime or support libraries to determine whether a particular use case is security sensitive or not, and while it’s straightforward for application developer to decide how to handle an exception thrown by a particular API, they can’t readily workaround an API blocking when they expected it to be non-blocking.

Accordingly, the PEP was updated to addsecrets.wait_for_system_rng()as an API for applications, scripts and frameworks to use to indicate that they wanted to ensure the system RNG was available before continuing, while library developers could continue to callos.urandom()without worrying that it might unexpectedly start blocking waiting for the system RNG to be available.

Unaffected Applications

The following kinds of applications would be entirely unaffected by the change, regardless of whether or not they perform security sensitive operations:

• applications that don’t support Linux
• applications that are only run on desktops or conventional servers
• applications that are only run after the system RNG is ready (including those where an application framework callssecrets.wait_for_system_rng() on their behalf)

Applications in this category simply won’t encounter the new exception, so it will be reasonable for developers to wait and see if they receive Python 3.6 compatibility bugs related to the new runtime behaviour, rather than attempting to pre-emptively determine whether or not they’re affected.

Affected security sensitive applications

Security sensitive applications would need to either change their system configuration so the application is only started after the operating system random number generator is ready for security sensitive operations, change the application startup code to invokesecrets.wait_for_system_rng(),or else switch to using the newsecrets.token_bytes()API.

As an example for components started via a systemd unit file, the following snippet would delay activation until the system RNG was ready:

ExecStartPre= Python 3 -c “import secrets; secrets.wait_for_system_rng()”

Alternatively, the following snippet will usesecrets.token_bytes()if available, and fall back toos.urandom()otherwise:

try:

import secrets.token_bytes as _get_random_bytes

except ImportError:

import os.urandom as _get_random_bytes

Affected non-security sensitive applications

Non-security sensitive applications should be updated to use therandom module rather thanos.urandom:

defpseudorandom_bytes(num_bytes):
returnrandom.getrandbits(num_bytes*8).to_bytes(num_bytes,"little")

Depending on the details of the application, the random module may offer other APIs that can be used directly, rather than needing to emulate the raw byte sequence produced by theos.urandom()API.

Why propose this now?

The main reason is because the Python 3.5.0 release switched to using the new Linuxgetrandom()syscall when available in order to avoid consuming a file descriptor[1],and this had the side effect of making the following operations block waiting for the system random number generator to be ready:

• os.urandom(and APIs that depend on it)
• importing therandommodule
• initializing the randomized hash algorithm used by some builtin types

While the first of those behaviours is arguably desirable (and consistent with the existing behaviour ofos.urandomon other operating systems), the latter two behaviours are unnecessary and undesirable, and the last one is now known to cause a system level deadlock when attempting to run Python scripts during the Linux init process with Python 3.5.0 or 3.5.1[2],while the second one can cause problems when using virtual machines without robust entropy sources configured[3].

Since decoupling these behaviours in CPython will involve a number of implementation changes more appropriate for a feature release than a maintenance release, the relatively simple resolution applied in Python 3.5.2 was to revert all three of them to a behaviour similar to that of previous Python versions: if the new Linux syscall indicates it will block, then Python 3.5.2 will implicitly fall back on reading/dev/urandomdirectly[4].

However, this bug reportalsoresulted in a range of proposals to addnew APIs likeos.getrandom()[5],os.urandom_block()[6], os.pseudorandom()andos.cryptorandom()[7],or adding new optional parameters toos.urandom()itself[8],and then attempting to educate users on when they should call those APIs instead of just using a plain os.urandom()call.

These proposals arguably represent overreactions, as the question of reliably obtaining random numbers suitable for security sensitive work on Linux is a relatively obscure problem of interest mainly to operating system developers and embedded systems programmers, that may not justify expanding the Python standard library’s cross-platform APIs with new Linux-specific concerns. This is especially so with thesecretsmodule already being added as the “use this and don’t worry about the low level details” option for developers writing security sensitive software that for some reason can’t rely on even higher level domain specific APIs (like web frameworks) and also don’t need to worry about Python versions prior to Python 3.6.

That said, it’s also the case that low cost ARM devices are becoming increasingly prevalent, with a lot of them running Linux, and a lot of folks writing Python applications that run on those devices. That creates an opportunity to take an obscure security problem that currently requires a lot of knowledge about Linux boot processes and provably unpredictable random number generation to diagnose and resolve, and instead turn it into a relatively mundane and easy-to-find-in-an-internet-search runtime exception.

The cross-platform behaviour ofos.urandom()

On operating systems other than Linux and NetBSD,os.urandom()may already block waiting for the operating system’s random number generator to be ready. This will happen at most once in the lifetime of the process, and the call is subsequently guaranteed to be non-blocking.

Linux and NetBSD are outliers in that, even when the operating system’s random number generator doesn’t consider itself ready for use in security sensitive operations, reading from the/dev/urandomdevice will return random values based on the entropy it has available.

This behaviour is potentially problematic, so Linux 3.17 added a new getrandom()syscall that (amongst other benefits) allows callers to either block waiting for the random number generator to be ready, or else request an error return if the random number generator is not ready. Notably, the new API doesnotsupport the old behaviour of returning data that is not suitable for security sensitive use cases.

Versions of Python prior up to and including Python 3.4 access the Linux/dev/urandomdevice directly.

Python 3.5.0 and 3.5.1 (when build on a system that offered the new syscall) calledgetrandom()in blocking mode in order to avoid the use of a file descriptor to access/dev/urandom.While there were no specific problems reported due toos.urandom()blocking in user code, therewereproblems due to CPython implicitly invoking the blocking behaviour during interpreter startup and when importing therandommodule.

Rather than trying to decouple SipHash initialization from the os.urandom()implementation, Python 3.5.2 switched to calling getrandom()in non-blocking mode, and falling back to reading from /dev/urandomif the syscall indicates it will block.

As a result of the above,os.urandom()in all Python versions up to and including Python 3.5 propagate the behaviour of the underling/dev/urandom device to Python code.

Problems with the behaviour of/dev/urandomon Linux

The Pythonosmodule has largely co-evolved with Linux APIs, so having osmodule functions closely follow the behaviour of their Linux operating system level counterparts when running on Linux is typically considered to be a desirable feature.

However,/dev/urandomrepresents a case where the current behaviour is acknowledged to be problematic, but fi xing it unilaterally at the kernel level has been shown to prevent some Linux distributions from booting (at least in part due to components like Python currently using it for non-security-sensitive purposes early in the system initialization process).

As an analogy, consider the following two functions:

defgenerate_example_password():
"""Generates passwords solely for use in code examples" ""
returngenerate_unpredictable_password()

defgenerate_actual_password():
"""Generates actual passwords for use in real applications" ""
returngenerate_unpredictable_password()

If you think of an operating system’s random number generator as a method for generating unpredictable, secret passwords, then you can think of Linux’s /dev/urandomas being implemented like:

# Oversimplified artist's conception of the kernel code
# implementing /dev/urandom
defgenerate_unpredictable_password():
ifsystem_rng_is_ready:
returnuse_system_rng_to_generate_password()
else:
# we can't make an unpredictable password; silently return a
# potentially predictable one instead:
return"p4ssw0rd"

In this scenario, the author ofgenerate_example_passwordis fine - even if "p4ssw0rd"shows up a bit more often than they expect, it’s only used in examples anyway. However, the author ofgenerate_actual_passwordhas a problem - how do they prove that their calls to generate_unpredictable_passwordnever follow the path that returns a predictable answer?

In real life it’s slightly more complicated than this, because there might be some level of system entropy available – so the fallback might be more likereturnrandom.choice([ "p4ssword","passw0rd", "p4ssw0rd" ])or something even more variable and hence only statistically predictable with better odds than the author ofgenerate_actual_password was expecting. This doesn’t really make things more provably secure, though; mostly it just means that if you try to catch the problem in the obvious way – ifreturned_password=="p4ssw0rd":raiseUhOh– then it doesn’t work, becausereturned_passwordmight instead bep4sswordor even pa55word,or just an arbitrary 64 bit sequence selected from fewer than 2**64 possibilities. So this rough sketch does give the right general idea of the consequences of the “more predictable than expected” fallback behaviour, even though it’s thoroughly unfair to the Linux kernel team’s efforts to mitigate the practical consequences of this problem without resorting to breaking backwards compatibility.

This design is generally agreed to be a bad idea. As far as we can tell, there are no use cases whatsoever in which this is the behavior you actually want. It has led to the use of insecuresshkeys on real systems, and many *nix-like systems (including at least Mac OS X, OpenBSD, and FreeBSD) have modified their/dev/urandom implementations so that they never return predictable outputs, either by making reads block in this case, or by simply refusing to run any userspace programs until the system RNG has been initialized. Unfortunately, Linux has so far been unable to follow suit, because it’s been empirically determined that enabling the blocking behavior causes some currently extant distributions to fail to boot.

Instead, the newgetrandom()syscall was introduced, making itpossiblefor userspace applications to access the system random number generator safely, without introducing hard to debug deadlock problems into the system initialization processes of existing Linux distros.

Consequences ofgetrandom()availability for Python

Prior to the introduction of thegetrandom()syscall, it simply wasn’t feasible to access the Linux system random number generator in a provably safe way, so we were forced to settle for reading from/dev/urandomas the best available option. However, withgetrandom()insisting on raising an error or blocking rather than returning predictable data, as well as having other advantages, it is now the recommended method for accessing the kernel RNG on Linux, with reading/dev/urandomdirectly relegated to “legacy” status. This moves Linux into the same category as other operating systems like Windows, which doesn’t provide a/dev/urandomdevice at all: the best available option for implementingos.urandom()is no longer simply reading bytes from the/dev/urandomdevice.

This means that what used to be somebody else’s problem (the Linux kernel development team’s) is now Python’s problem – given a way to detect that the system RNG is not initialized, we have to choose how to handle this situation whenever we try to use the system RNG.

It could simply block, as was somewhat inadvertently implemented in 3.5.0, and as is proposed in Victor Stinner’s competing PEP:

# artist's impression of the CPython 3.5.0-3.5.1 behavior
defgenerate_unpredictable_bytes_or_block(num_bytes):
whilenotsystem_rng_is_ready:
wait
returnunpredictable_bytes(num_bytes)

Or it could raise an error, as this PEP proposes (insomecases):

# artist's impression of the behavior proposed in this PEP
defgenerate_unpredictable_bytes_or_raise(num_bytes):
ifsystem_rng_is_ready:
returnunpredictable_bytes(num_bytes)
else:
raiseBlockingIOError

Or it could explicitly emulate the/dev/urandomfallback behavior, as was implemented in 3.5.2rc1 and is expected to remain for the rest of the 3.5.x cycle:

# artist's impression of the CPython 3.5.2rc1+ behavior
defgenerate_unpredictable_bytes_or_maybe_not(num_bytes):
ifsystem_rng_is_ready:
returnunpredictable_bytes(num_bytes)
else:
return(b"p4ssw0rd"*(num_bytes//8+1))[:num_bytes]

(And the same caveats apply to this sketch as applied to the generate_unpredictable_passwordsketch of/dev/urandomabove.)

There are five places where CPython and the standard library attempt to use the operating system’s random number generator, and thus five places where this decision has to be made:

• initializing the SipHash used to protectstr.__hash__and friends against DoS attacks (called unconditionally at startup)
• initializing therandommodule (called whenrandomis imported)
• servicing user calls to theos.urandompublic API
• the higher levelrandom.SystemRandompublic API
• the newsecretsmodule public API added byPEP 506

Previously, these five places all used the same underlying code, and thus made this decision in the same way.

This whole problem was first noticed because 3.5.0 switched that underlying code to thegenerate_unpredictable_bytes_or_blockbehavior, and it turns out that there are some rare cases where Linux boot scripts attempted to run a Python program as part of system initialization, the Python startup sequence blocked while trying to initialize SipHash, and then this triggered a deadlock because the system stopped doing anything – including gathering new entropy – until the Python script was forcibly terminated by an external timer. This is particularly unfortunate since the scripts in question never processed untrusted input, so there was no need for SipHash to be initialized with provably unpredictable random data in the first place. This motivated the change in 3.5.2rc1 to emulate the old /dev/urandombehavior in all cases (by callinggetrandom()in non-blocking mode, and then falling back to reading/dev/urandom if the syscall indicates that the/dev/urandompool is not yet fully initialized.)

We don’t know whether such problems may also exist in the Fedora/RHEL/CentOS ecosystem, as the build systems for those distributions use chroots on servers running an older operating system kernel that doesn’t offer thegetrandom() syscall, which means CPython’s current build configuration compiles out the runtime check for that syscall[10].

A similar problem was found due to therandommodule calling os.urandomas a side-effect of import in order to seed the default globalrandom.Random()instance.

We have not received any specific complaints regarding direct calls to os.urandom()orrandom.SystemRandom()blocking with 3.5.0 or 3.5.1 - only problem reports due to the implicit blocking on interpreter startup and as a side-effect of importing the random module.

Independently of this PEP, the first two cases have already been updated to never block, regardless of the behaviour ofos.urandom().

WherePEP 524proposes to make all 3 of the latter cases block implicitly, this PEP proposes that approach only for the last case (thesecrets) module, withos.urandom()andrandom.SystemRandom()instead raising an exception when they detect that the underlying operating system call would block.