Why Raspberry Pi isn’t exposed to Spectre or Meltdown

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Over a final integrate of days, there has been a lot of contention about a span of confidence vulnerabilities nicknamed Spectre and Meltdown. These impact all complicated Intel processors, and (in a box of Spectre) many AMD processors and ARM cores. Spectre allows an assailant to bypass module checks to review information from capricious locations in a tide residence space; Meltdown allows an assailant to review capricious information from a handling complement kernel’s residence space (which should routinely be untouched to user programs).

Both vulnerabilities feat opening facilities (caching and suppositional execution) common to many complicated processors to trickle information around a supposed side-channel attack. Happily, a Raspberry Pi isn’t receptive to these vulnerabilities, since of a sold ARM cores that we use.

To assistance us know why, here’s a tiny authority on some concepts in complicated processor design. We’ll illustrate these concepts regulating elementary programs in Python syntax like this one:

t = a+b
u = c+d
v = e+f
w = v+g
x = h+i
y = j+k

While a processor in your mechanism doesn’t govern Python directly, a statements here are elementary adequate that they roughly conform to a singular appurtenance instruction. We’re going to shimmer over some sum (notably pipelining and register renaming) that are really critical to processor designers, yet that aren’t compulsory to know how Spectre and Meltdown work.

For a extensive outline of processor design, and other aspects of complicated mechanism architecture, we can’t do improved than Hennessy and Patterson’s classical Computer Architecture: A Quantitative Approach.

What is a scalar processor?

The simplest arrange of complicated processor executes one instruction per cycle; we call this a scalar processor. Our instance above will govern in 6 cycles on a scalar processor.

Examples of scalar processors embody a Intel 486 and a ARM1176 core used in Raspberry Pi 1 and Raspberry Pi Zero.

What is a superscalar processor?

The apparent proceed to make a scalar processor (or indeed any processor) run faster is to boost a time speed. However, we shortly strech boundary of how quick a proof gates inside a processor can be done to run; processor designers therefore fast began to demeanour for ways to do several things during once.

An in-order superscalar processor examines a incoming tide of instructions and tries govern some-more than one during once, in one of several “pipes”, theme to dependencies between a instructions. Dependencies are important: we competence consider that a two-way superscalar processor could usually span adult (or dual-issue) a 6 instructions in a instance like this:

t, u = a+b, c+d
v, w = e+f, v+g
x, y = h+i, j+k

But this doesn’t make sense: we have to discriminate v before we can discriminate w, so a third and fourth instructions can’t be executed during a same time. Our two-way superscalar processor won’t be means to find anything to span with a third instruction, so a instance will govern in 4 cycles:

t, u = a+b, c+d
v    = e+f                   # second siren does 0 here
w, x = v+g, h+i
y    = j+k

Examples of superscalar processors embody a Intel Pentium, and a ARM Cortex-A7 and Cortex-A53 cores used in Raspberry Pi 2 and Raspberry Pi 3 respectively. Raspberry Pi 3 has usually a 33% aloft time speed than Raspberry Pi 2, yet has roughly double a performance: a additional opening is partly a outcome of Cortex-A53’s ability to dual-issue a broader operation of instructions than Cortex-A7.

What is an out-of-order processor?

Going behind to a example, we can see that, nonetheless we have a dependency between v and w, we have other eccentric instructions after in a module that we could potentially have used to fill a dull siren during a second cycle. An out-of-order superscalar processor has a ability to trifle a sequence of incoming instructions (again theme to dependencies) in sequence to keep a pipelines busy.

An out-of-order processor competence effectively barter a definitions of w and x in a instance like this:

t = a+b
u = c+d
v = e+f
x = h+i
w = v+g
y = j+k

allowing it to govern in 3 cycles:

t, u = a+b, c+d
v, x = e+f, h+i
w, y = v+g, j+k

Examples of out-of-order processors embody a Intel Pentium 2 (and many successive Intel and AMD x86 processors), and many new ARM cores, including Cortex-A9, -A15, -A17, and -A57.

What is speculation?

Reordering consecutive instructions is a absolute proceed to redeem some-more instruction-level parallelism, yet as processors spin wider (able to triple- or quadruple-issue instructions) it becomes harder to keep all those pipes busy. Modern processors have therefore grown a ability to speculate. Speculative execution lets us emanate instructions that competence spin out not to be compulsory (because they are branched over): this keeps a siren busy, and if it turns out that a instruction isn’t executed, we can usually chuck a outcome away.

To denote a advantages of speculation, let’s demeanour during another example:

t = a+b
u = t+c
v = u+d
if v:
   w = e+f
   x = w+g
   y = x+h

Now we have dependencies from t to u to v, and from w to x to y, so a two-way out-of-order processor yet conjecture won’t ever be means to fill a second pipe. It spends 3 cycles computing t, u, and v, after that it knows possibly a physique of a if matter will execute, in that box it afterwards spends 3 cycles computing w, x, and y. Assuming a if (a bend instruction) takes one cycle, a instance takes possibly 4 cycles (if v turns out to be zero) or 7 cycles (if v is non-zero).

Speculation effectively shuffles a module like this:

t = a+b
u = t+c
v = u+d
w_ = e+f
x_ = w_+g
y_ = x_+h
if v:
   w, x, y = w_, x_, y_

so we now have additional instruction turn correspondence to keep a pipes busy:

t, w_ = a+b, e+f
u, x_ = t+c, w_+g
v, y_ = u+d, x_+h
if v:
   w, x, y = w_, x_, y_

Cycle counting becomes reduction good tangible in suppositional out-of-order processors, yet a bend and redeeming refurbish of w, x, and y are (approximately) free, so a instance executes in (approximately) 3 cycles.

What is a cache?

In a good aged days*, a speed of processors was good matched with a speed of memory access. My BBC Micro, with a 2MHz 6502, could govern an instruction roughly each 2µs (microseconds), and had a memory cycle time of 0.25µs. Over a indirect 35 years, processors have spin really most faster, yet memory usually modestly so: a singular Cortex-A53 in a Raspberry Pi 3 can govern an instruction roughly each 0.5ns (nanoseconds), yet can take adult to 100ns to entrance categorical memory.

At initial glance, this sounds like a disaster: each time we entrance memory, we’ll finish adult watchful for 100ns to get a outcome back. In this case, this example:

a = mem[0]
b = mem[1]

would take 200ns.

In practice, programs tend to entrance memory in comparatively predicted ways, exhibiting both temporal locality (if we entrance a location, I’m expected to entrance it again soon) and spatial locality (if we entrance a location, I’m expected to entrance a circuitously plcae soon). Caching takes advantage of these properties to revoke a normal cost of entrance to memory.

A cache is a tiny on-chip memory, tighten to a processor, that stores copies of a essence of recently used locations (and their neighbours), so that they are fast permitted on successive accesses. With caching, a instance above will govern in a tiny over 100ns:

a = mem[0]    # 100ns delay, copies mem[0:15] into cache
b = mem[1]    # mem[1] is in a cache

From a indicate of perspective of Spectre and Meltdown, a critical indicate is that if we can time how prolonged a memory entrance takes, we can establish possibly a residence we accessed was in a cache (short time) or not (long time).

What is a side channel?

From Wikipedia:

“… a side-channel conflict is any conflict formed on information gained from a earthy doing of a cryptosystem, rather than beast force or fanciful weaknesses in a algorithms (compare cryptanalysis). For example, timing information, energy consumption, electromagnetic leaks or even sound can yield an additional source of information, that can be exploited to mangle a system.”

Spectre and Meltdown are side-channel attacks that ascertain a essence of a memory plcae that should not routinely be permitted by regulating timing to observe possibly another plcae is benefaction in a cache.

Putting it all together

Now let’s demeanour during how conjecture and caching mix to assent a Meltdown attack. Consider a following example, that is a user module that infrequently reads from an bootleg (kernel) address:

t = a+b
u = t+c
v = u+d
if v:
   w = kern_mem
# if we get here crash x = w0x100 y = user_mem[x]

Now a out-of-order two-way superscalar processor shuffles a module like this:

t, w_ = a+b, kern_mem
u, x_ = t+c, w_0x100 v, y_ = u+d, user_mem[x_] if v: # crash w, x, y = w_, x_, y_ # we never get here

Even yet a processor always speculatively reads from a heart address, it contingency defer a ensuing error until it knows that v was non-zero. On a face of it, this feels protected since either:

  • v is zero, so a outcome of a bootleg review isn’t committed to w
  • v is non-zero, so a module crashes before a review is committed to w

However, suspect we flush a cache before executing a code, and arrange a, b, c, and d so that v is zero. Now, a suppositional bucket in a third cycle:

v, y_ = u+d, user_mem[x_]

will review from possibly residence 0x000 or residence 0x100 depending on a eighth bit of a outcome of a bootleg read. Because v is zero, a formula of a suppositional instructions will be discarded, and execution will continue. If we time a successive entrance to one of those addresses, we can establish that residence is in a cache. Congratulations: you’ve usually review a singular bit from a kernel’s residence space!

The genuine Meltdown feat is some-more formidable than this, yet a element is a same. Spectre uses a identical proceed to mishandle module array end checks.


Modern processors go to good lengths to safety a condensation that they are in-order scalar machines that entrance memory directly, while in fact regulating a horde of techniques including caching, instruction reordering, and conjecture to broach most aloft opening than a elementary processor could wish to achieve. Meltdown and Spectre are examples of what happens when we reason about confidence in a context of that abstraction, and afterwards confront teenager discrepancies between a condensation and reality.

The miss of conjecture in a ARM1176, Cortex-A7, and Cortex-A53 cores used in Raspberry Pi describe us defence to attacks of a sort.

* days might not be that old, or that good

Source: Raspberry Pi blog, created by Eben Upton.

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