Meltdown Paper

本文主要内容来自郭健(http://www.wowotech.net/basic_subject/meltdown.html)翻译。

• Moritz Lipp: Homepage, Github, Dblp, Twitter
• Michael Schwarz: Homepage, Github
• Daniel Gruss: Homepage, Github
• Thomas Prescher: Dblp
• Werner Haas: Dblp
• Stefan Mangard: Dblp
• Paul Kocher
• Daniel Genkin
• Yuval Yarom
• Mike Hamburg

The security of computer systems fundamentally relies on memory isolation, e.g., kernel address ranges are marked as non-accessible and are protected from user access. In this paper, we present Meltdown. Meltdown exploits side effects of out-of-order execution on modern processors to read arbitrary kernel-memory locations including personal data and passwords. Out-of-order execution is an indispensable(必不可少的) performance feature and present in a wide range of modern processors. The attack is independent of the operating system, and it does not rely on any software vulnerabilities. Meltdown breaks all security assumptions given by address space isolation as well as paravirtualized environments and, thus, every security mechanism building upon this foundation. On affected systems, Meltdown enables an adversary(敌对者) to read memory of other processes or virtual machines in the cloud without any permissions or privileges, affecting millions of customers and virtually every user of a personal computer. We show that the KAISER defense mechanism for KASLR [8] has the important (but inadvertent) side effect of impeding Meltdown. We stress that KAISER must be deployed immediately to prevent large-scale exploitation of this severe information leakage.

内存隔离是计算机系统安全的基础，例如：内核空间的地址段往往是标记为受保护的，用户 态程序读写内核地址则会触发异常，从而阻止其访问。在这篇文章中，我们会详细描述这个 叫Meltdown的硬件漏洞。Meltdown是利用了现代处理器上乱序执行（out-of-order execution）的副作用（side effect），使得用户态程序也可以读出内核空间的数据，包括 个人私有数据和密码。由于可以提高性能，现代处理器广泛采用了乱序执行特性。利用 Meltdown进行攻击的方法和操作系统无关，也不依赖于软件的漏洞。地址空间隔离带来的 安全保证被Meltdown给无情的打碎了（半虚拟化环境也是如此），因此，所有基于地址空间 隔离的安全机制都不再安全了。在受影响的系统中，Meltdown可以让一个攻击者读取其他 进程的数据，或者读取云服务器中其他虚拟机的数据，而不需要相应的权限。这份文档也 说明了KAISER（本意是解决KASLR不能解决的问题）可以防止Meltdown攻击。因此，我们 强烈建议必须立即部署KAISER，以防止大规模、严重的信息泄漏。

One of the central security features of today’s operating systems is memory isolation. Operating systems ensure that user applications cannot access each other’s memories and prevent user applications from reading or writing kernel memory. This isolation is a cornerstone of our computing environments and allows running multiple applications on personal devices or executing processes of multiple users on a single machine in the cloud.

当今操作系统的核心安全特性之一是内存隔离。所谓内存隔离就是操作系统要确保用户应用 程序不能访问彼此的内存，此外，它也要阻止用户应用程序对内核空间的访问。在个人设备 上，多个进程并行运行，我们需要隔离彼此。在云计算环境中，共享同一台物理主机的多个 用户（虚拟机）的多个进程也是共存的，我们也不能让某个用户（虚拟机）的进程能够访问 到其他用户（虚拟机）的进程数据。因此，这种内核隔离是我们计算环境的基石。

On modern processors, the isolation between the kernel and user processes is typically realized by a supervisor bit of the processor that defines whether a memory page of the kernel can be accessed or not. The basic idea is that this bit can only be set when entering kernel code and it is cleared when switching to user processes. This hardware feature allows operating systems to map the kernel into the address space of every process and to have very efficient transitions from the user process to the kernel, e.g., for interrupt handling. Consequently, in practice, there is no change of the memory mapping when switching from a user process to the kernel.

在现代处理器上，内核和用户地址空间的隔离通常由处理器控制寄存器中的一个bit实现（ 该bit被称为supervisor bit，标识当前处理器处于的模式），该bit定义了是否可以访问 kernel space的内存页。基本的思路是：当执行内核代码的时候才设置此位等于1，在切换 到用户进程时清除该bit。有了这种硬件特性的支持，操作系统可以将内核地址空间映射到 每个进程。在用户进程执行过程中，往往需要从用户空间切换到内核空间，例如用户进程 通过系统调用请求内核空间的服务，或者当在用户空间发生中断的时候，需要切换到内核 空间执行interrupt handler，以便来处理外设的异步事件。考虑到从用户态切换内核态的 频率非常高，如果在这个过程中地址空间不需要切换，那么系统性能就不会受到影响。

In this work, we present Meltdown¹. Meltdown is a novel attack that allows overcoming memory isolation completely by providing a simple way for any user process to read the entire kernel memory of the machine it executes on, including all physical memory mapped in the kernel region. Meltdown does not exploit any software vulnerability, i.e., it works on all major operating systems. Instead, Meltdown exploits side-channel information available on most modern processors, e.g., modern Intel microarchitectures since 2010 and potentially on other CPUs of other vendors.

在这项工作中，我们提出了利用meltdown漏洞进行攻击的一种全新的方法，通过这种方法， 任何用户进程都可以攻破操作系统对地址空间的隔离，通过一种简单的方法读取内核空间的 数据，这里就包括映射到内核地址空间的所有的物理内存。Meltdown并不利用任何的软件的 漏洞，也就是说它对任何一种操作系统都是有效的。相反，它是利用大多数现代处理器（ 例如2010年以后的Intel微架构（microarchitectural），其他CPU厂商也可能潜伏这样的 问题）上的侧信道（side-channel）信息来发起攻击。

While side-channel attacks typically require very specific knowledge about the target application and are tailored to only leak information about its secrets, Meltdown allows an adversary who can run code on the vulnerable processor to obtain a dump of the entire kernel address space, including any mapped physical memory. The root cause of the simplicity and strength of Meltdown are side effects caused by out-of-order execution.

一般的侧信道攻击（side-channel attack）都需要直到攻击目标的详细信息，然后根据 这些信息指定具体的攻击方法，从而获取秘密数据。Meltdown攻击方法则不然，它可以dump 整个内核地址空间的数据（包括全部映射到内核地址空间的物理内存）。Meltdown攻击力度 非常很大，其根本原因是利用了乱序执行的副作用（side effect）。

Out-of-order execution is an important performance feature of today’s processors in order to overcome latencies of busy execution units, e.g., a memory fetch unit needs to wait for data arrival from memory. Instead of stalling the execution, modern processors run operations out-of-order i.e., they look ahead and schedule subsequent operations to idle execution units of the processor. However, such operations often have unwanted side-effects, e.g., timing differences ^{2 , 3 , 4} can leak information from both sequential and out-of-order execution.

乱序执行是当今CPU的重要性能特性，用以克服繁忙执行单元的延时，例如加载内存数据到 寄存器这样的操作。为了提高性能，CPU并不是进入stall状态，而是采用了乱序执行的 方法，继续处理后续指令并调度该指令去空闲的执行单元去执行。然而，这种操作常常有 不必要的副作用，而通过这些执行指令时候的副作用，例如时序方面的差异 ²

四、Meltdown攻击架构图（Building block of attack）

The toy example in Section 3 illustrated that side-effects of out-of-order execution can modify the microarchitectural state to leak information. While the code snippet reveals the data value passed to a cache-side channel, we want to show how this technique can be leveraged to leak otherwise inaccessible secrets. In this section, we want to generalize and discuss the necessary building blocks to exploit out-of-order execution for an attack.

上一章中我们通过简单的示例代码展示了乱序执行的副作用会修改微架构状态，从而造成信息泄露。通过代码片段我们已经看到了data变量值已经传递到缓存侧通道上，下面我们会详述如何利用这种技术来泄漏受保护的数据。在本章中，我们将概括并讨论利用乱序执行进行攻击所需要的组件。

The adversary targets a secret value that is kept somewhere in physical memory. Note that register contents are also stored in memory upon context switches, i.e., they are also stored in physical memory. As described in Section 2.2, the address space of every process typically includes the entire user space, as well as the entire kernel space, which typically also has all physical memory (inuse) mapped. However, these memory regions are only accessible in privileged mode (cf. Section 2.2).

攻击者的目标是保存在物理内存中的一个秘密值。注意：寄存器值也会在上下文切换时保存在物理内存中。根据2.2节所述，每个进程的地址空间通常包括整个用户地址空间以及整个内核地址空间（使用中的物理内存都会映射到该空间中），虽然进程能感知到内核空间的映射。但是这些内存区域只能在特权模式下访问（参见第2.2节）。

In this work, we demonstrate leaking secrets by bypassing the privileged-mode isolation, giving an attacker full read access to the entire kernel space including any physical memory mapped, including the physical memory of any other process and the kernel. Note that Kocher et al. [19] pursue an orthogonal approach, called Spectre Attacks, which trick speculative executed instructions into leaking information that the victim process is authorized to access. As a result, Spectre Attacks lack the privilege escalation aspect of Meltdown and require tailoring to the victim process’s software environment, but apply more broadly to CPUs that support speculative execution and are not stopped by KAISER.

在这项工作中，我们绕过了地址空间隔离机制，让攻击者可以对整个内核空间进行完整的读访问，这里面就包括物理内存直接映射部分。而通过直接映射，攻击者可以访问任何其他进程和内核的物理内存。注意：Kocher等人[ 19 ]正在研究一种称为幽灵（spectre）攻击的方法，它通过推测执行（speculative execution）来泄漏目标进程的秘密信息。因此，幽灵攻击不涉及Meltdown攻击中的特权提升，并且需要根据目标进程的软件环境进行定制。不过spectre会影响更多的CPU（只要支持speculative execution的CPU都会受影响），另外，KAISER无法阻挡spectre攻击。

The full Meltdown attack consists of two building blocks, as illustrated in Figure 5. The first building block of Meltdown is to make the CPU execute one or more instructions that would never occur in the executed path. In the toy example (cf. Section 3), this is an access to an array, which would normally never be executed, as the previous instruction always raises an exception. We call such an instruction, which is executed out of order, leaving measurable side effects, a transient instruction. Furthermore, we call any sequence of instructions containing at least one transient instruction a transient instruction sequence.

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完整的meltdown攻击由两个组件构成，如上图所示。第一个组件是使CPU执行一个或多个在正常路径中永远不会执行的指令。在第三章中的简单示例代码中，对数组的访问指令按理说是不会执行，因为前面的指令总是触发异常。我们称这种指令为瞬态指令（transient instruction），瞬态指令在乱序执行的时候被CPU执行（正常情况下不会执行），留下可测量的副作用。此外，我们把任何包含至少一个瞬态指令的指令序列称为瞬态指令序列。

In order to leverage transient instructions for an attack, the transient instruction sequence must utilize a secret value that an attacker wants to leak. Section 4.1 describes building blocks to run a transient instruction sequence with a dependency on a secret value.

为了使用瞬态指令来完成攻击，瞬态指令序列必须访问攻击者想要获取的秘密值并加以利用。第4.1节将描述一段瞬态指令序列，我们会仔细看看这段指令会如何使用受保护的数据。

The second building block of Meltdown is to transfer the microarchitectural side effect of the transient instruction sequence to an architectural state to further process the leaked secret. Thus, the second building described in Section 4.2 describes building blocks to transfer a microarchitectural side effect to an architectural state using a covert channel.

Meltdown的第二个组件主要用来检测在瞬态指令序列执行完毕之后，在CPU微架构上产生的side effect。并将其转换成软件可以感知的CPU体系结构的状态，从而将数据泄露出来。因此，在4.2节中描述的第二个组件主要是使用隐蔽信道来把CPU微架构的副作用转换成CPU architectural state。

1、执行瞬态指令（executing transient instructions）

The first building block of Meltdown is the execution of transient instructions. Transient instructions basically occur all the time, as the CPU continuously runs ahead of the current instruction to minimize the experienced latency and thus maximize the performance (cf. Section 2.1). Transient instructions introduce an exploitable side channel if their operation depends on a secret value. We focus on addresses that are mapped within the attacker’s process, i.e., the user-accessible user space addresses as well as the user-inaccessible kernel space addresses. Note that attacks targeting code that is executed

within the context (i.e., address space) of another process are possible [19], but out of scope in this work, since all physical memory (including the memory of other processes) can be read through the kernel address space anyway.

Meltdown的第一个组件是执行瞬态指令。其实瞬态指令是时时刻刻都在发生的，因为CPU在执行当前指令之外，往往会提前执行当前指令之后的那些指令，从而最大限度地提高CPU性能（参见第2.1节的描述）。如果瞬态指令的执行依赖于一个受保护的值，那么它就引入一个可利用的侧信道。另外需要说明的是：本文主要精力放在攻击者的进程地址空间中，也就是说攻击者在用户态访问内核地址空间的受保护的数据。实际上攻击者进程访问盗取其他进程地址空间的数据也是可能的（不过本文并不描述这个场景），毕竟攻击者进程可以通过内核地址空间访问系统中所有内存，而其他进程的数据也就是保存在系统物理内存的某个地址上。

Accessing user-inaccessible pages, such as kernel pages, triggers an exception which generally terminates the application. If the attacker targets a secret at a user inaccessible address, the attacker has to cope with this exception. We propose two approaches: With exception handling, we catch the exception effectively occurring after executing the transient instruction sequence, and with exception suppression, we prevent the exception from occurring at all and instead redirect the control flow after executing the transient instruction sequence. We discuss these approaches in detail in the following.

运行于用户态时访问特权页面，例如内核页面，会触发一个异常，该异常通常终止应用程序。如果攻击者的目标是一个内核空间地址中保存的数据，那么攻击者必须处理这个异常。我们提出两种方法：一种方法是设置异常处理函数，在发生异常的时候会调用该函数（这时候已经完成了瞬态指令序列的执行）。第二种方法是抑制异常的触发，下面我们将详细讨论这些方法。

Exception handling. A trivial approach is to fork the attacking application before accessing the invalid memory location that terminates the process, and only access the invalid memory location in the child process. The CPU executes the transient instruction sequence in the child process before crashing. The parent process can then recover the secret by observing the microarchitectural state, e.g., through a side-channel.

程序自己定义异常处理函数。

一个简单的方法是在访问内核地址（这个操作会触发异常并中止程序的执行）之前进行fork的操作，并只在子进程中访问内核地址，触发异常。在子进程crash之前，CPU已经执行了瞬态指令序列。在父进程中可以通过观察CPU微架构状态来盗取内核空间的数据。

It is also possible to install a signal handler that will be executed if a certain exception occurs, in this specific case a segmentation fault. This allows the attacker to issue the instruction sequence and prevent the application from crashing, reducing the overhead as no new process has to be created.

当然，你也可以设置信号处理函数。异常触发后将执行该信号处理函数（在这个场景下，异常是segmentation fault）。这种方法的好处是应用程序不会crash，不需要创建新进程，开销比较小。

Exception suppression.

这种方法和Transactional memory相关，有兴趣的同学可以自行阅读原文。

2、构建隐蔽通道（building covert channel）

The second building block of Meltdown is the transfer of the microarchitectural state, which was changed by the transient instruction sequence, into an architectural state (cf. Figure 5). The transient instruction sequence can be seen as the sending end of a microarchitectural covert channel. The receiving end of the covert channel receives the microarchitectural state change and deduces the secret from the state. Note that the receiver is not part of the transient instruction sequence and can be a different thread or even a different process e.g., the parent process in the fork-and-crash approach.

第二个Meltdown组件主要是用来把执行瞬态指令序列后CPU微架构状态变化的信息转换成相应的体系结构状态（参考上图）。瞬态指令序列可以认为是微架构隐蔽通道的发端，通道的接收端用来接收微架构状态的变化信息，从这些状态变化中推导出被保护的数据。需要注意的是：接收端并不是瞬态指令序列的一部分，可以来自其他的线程甚至是其他的进程。例如上节我们使用fork的那个例子中，瞬态指令序列在子进程中，而接收端位于父进程中

We leverage techniques from cache attacks, as the cache state is a microarchitectural state which can be reliably transferred into an architectural state using various techniques [28, 35, 10]. Specifically, we use Flush+Reload [35], as it allows to build a fast and low-noise covert channel. Thus, depending on the secret value, the transient instruction sequence (cf. Section 4.1) performs a regular memory access, e.g., as it does in the toy example (cf. Section 3).

我们可以利用缓存攻击（cache attack）技术，通过对高速缓存的状态（是微架构状态之一）的检测，我们可以使用各种技术[ 28, 35, 10 ]将其稳定地转换成CPU体系结构状态。具体来说，我们可以使用Flush+Reload技术 [35]，因为该技术允许建立一个快速的、低噪声的隐蔽通道。然后根据保密数据，瞬态指令序列（参见第4.1节）执行常规的存储器访问，具体可以参考在第3节给出的那个简单示例程序中所做的那样。

After the transient instruction sequence accessed an accessible address, i.e., this is the sender of the covert channel; the address is cached for subsequent accesses. The receiver can then monitor whether the address has been loaded into the cache by measuring the access time to the address. Thus, the sender can transmit a ‘1’-bit by accessing an address which is loaded into the monitored cache, and a ‘0’-bit by not accessing such an address.

在隐蔽通道的发送端，瞬态指令序列会访问一个普通内存地址，从而导致该地址的数据被加载到了cache（为了加速后续访问）。然后，接收端可以通过测量内存地址的访问时间来监视数据是否已加载到缓存中。因此，发送端可以通过访问内存地址（会加载到cache中）传递bit 1的信息，或者通过不访问内存地址（不会加载到cache中）来发送bit 0信息。而接收端可以通过监视cache的信息来接收这个bit 0或者bit 1的信息。

Using multiple different cache lines, as in our toy example in Section 3, allows to transmit multiple bits at once. For every of the 256 different byte values, the sender accesses a different cache line. By performing a Flush+Reload attack on all of the 256 possible cache lines, the receiver can recover a full byte instead of just one bit. However, since the Flush+Reload attack takes much longer (typically several hundred cycles) than the transient instruction sequence, transmitting only a single bit at once is more efficient. The attacker can simply do that by shifting and masking the secret value accordingly.

使用一个cacheline可以传递一个bit，如果使用多个不同的cacheline（类似我们在第3章中的简单示例代码一样），就可以同时传输多个比特。一个Byte（8-bit）有256个不同的值，针对每一个值，发送端都会访问不同的缓存行，这样通过对所有256个可能的缓存行进行Flush+Reload攻击，接收端可以恢复一个完整字节而不是一个bit。不过，由于Flush+Reload攻击所花费的时间比执行瞬态指令序列要长得多（通常是几百个cycle），所以只传输一个bit是更有效的。攻击者可以通过shift和mask来完成保密数据逐个bit的盗取。

Note that the covert channel is not limited to microarchitectural states which rely on the cache. Any microarchitectural state which can be influenced by an instruction (sequence) and is observable through a side channel can be used to build the sending end of a covert channel. The sender could, for example, issue an instruction (sequence) which occupies a certain execution port such as the ALU to send a ‘1’-bit. The receiver measures the latency when executing an instruction (sequence) on the same execution port. A high latency implies that the sender sends a ‘1’-bit, whereas a low latency implies that sender sends a ‘0’-bit. The advantage of the Flush+ Reload cache covert channel is the noise resistance and the high transmission rate [10]. Furthermore, the leakage can be observed from any CPU core [35], i.e., rescheduling events do not significantly affect the covert channel.

需要注意的是：隐蔽信道并非总是依赖于缓存。只要CPU微架构状态会被瞬态指令序列影响，并且可以通过side channel观察这个状态的改变，那么该微架构状态就可以用来构建隐蔽通道的发送端。例如，发送端可以执行一条指令（该指令会占用相关执行单元（如ALU）的端口），来发送一个“1”这个bit。接收端可以在同一个执行单元端口上执行指令，同时测量时间延迟。高延迟意味着发送方发送一个“1”位，而低延迟意味着发送方发送一个“0”位。Flush+ Reload隐蔽通道的优点是抗噪声和高传输速率[ 10 ]。此外，我们可以从任何cpu core上观察到数据泄漏[ 35 ]，即调度事件并不会显著影响隐蔽信道。

五、熔断（Meltdown）

In this section, present Meltdown, a powerful attack allowing to read arbitrary physical memory from an unprivileged user program, comprised of the building blocks presented in Section 4. First, we discuss the attack setting to emphasize the wide applicability of this attack. Second, we present an attack overview, showing how Meltdown can be mounted on both Windows and Linux on personal computers as well as in the cloud. Finally, we discuss a concrete implementation of Meltdown allowing to dump kernel memory with up to 503KB/s.

在这一章我们将向您展示meltdown的威力：通过一个普通的用户程序读取系统中任意位置的物理内存。整个攻击过程的框架图已经在第4章描述。首先，我们讨论攻击设置，通过设置我们可以看出meltdown这种攻击具有非常广泛的适用性。其次，我们对meltdown攻击进行概述，并展示了它如何对安装Windows和Linux的个人计算机上以及云服务器展开攻击。最后，我们讨论了一个具体的实现，该Meltdown的实现允许以503kB／s的速度dump内核空间的内存。

Attack setting.

In our attack, we consider personal computers and virtual machines in the cloud. In the attack scenario, the attacker has arbitrary unprivileged code execution on the attacked system, i.e., the attacker can run any code with the privileges of a normal user. However, the attacker has no physical access to the machine. Further, we assume that the system is fully protected with state-of-the-art software-based defenses such as ASLR and KASLR as well as CPU features like SMAP, SMEP, NX, and PXN. Most importantly, we assume a completely bug-free operating system, thus, no software vulnerability exists that can be exploited to gain kernel privileges or leak information. The attacker targets secret user data, e.g., passwords and private keys, or any other valuable information.

攻击设定如下：

我们考虑个人计算机和云服务器上的虚拟机两种应用场景。在攻击过程中，攻击者只使用未授权的代码来攻击系统，也就是说攻击者只能以一个普通用户的权限来运行代码。另外，攻击者没有对机器进行物理访问。进一步，我们假设我们准备攻击的系统是已经有了非常好的基于软件的防御措施，例如ASLR和KASLR，同时CPU也包含了像SMAP，SMEP，NX，和PXN的功能。最重要的是，我们假设被攻击系统是一个完全无bug的操作系统，没有软件漏洞可以被利用来获得root权限或泄露信息。攻击者的目标是用户的秘密数据，例如密码和私钥，或任何其他有价值的信息。

1、概述

Meltdown combines the two building blocks discussed in Section 4. First, an attacker makes the CPU execute a transient instruction sequence which uses an inaccessible secret value stored somewhere in physical memory (cf. Section 4.1). The transient instruction sequence acts as the transmitter of a covert channel (cf. Section 4.2), ultimately leaking the secret value to the attacker.

Meltdown使用了第4章中讨论攻击架构图。首先，攻击者让CPU执行一个瞬态指令序列，该指令序列会操作保存在物理内存中不可访问的秘密数据（参见第4.1节）。瞬态指令序列充当隐蔽通道的发送端（参见第4.2节），最终将秘密数据泄漏给攻击者。

Meltdown consists of 3 steps:

Step 1 The content of an attacker-chosen memory location,which is inaccessible to the attacker, is loaded into a register.

Step 2 A transient instruction accesses a cache line based on the secret content of the register.

Step 3 The attacker uses Flush+Reload to determine the accessed cache line and hence the secret stored at the chosen memory location.

By repeating these steps for different memory locations, the attacker can dump the kernel memory, including the entire physical memory.

Meltdown攻击包括3个步骤：

步骤1：攻击者访问秘密数据所在的内存位置（该内存是攻击者没有权限访问的），并加载到一个寄存器中。

步骤2，瞬态指令基于寄存器中保存的秘密数据内容访问cache line。

步骤3：攻击者使用Flush+Reload来确定在步骤2中访问的cache line，从而恢复在步骤1中读取的秘密数据。

在不同的内存地址上不断重复上面的步骤，攻击者可以dump整个内核地址空间的数据，这也就包括了整个物理内存。

Listing 2 shows the basic implementation of the transient instruction sequence and the sending part of the covert channel, using x86 assembly instructions. Note that this part of the attack could also be implemented entirely in higher level languages like C. In the following, we will discuss each step of Meltdown and the corresponding code line in Listing 2.

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上面的列表显示了瞬态指令序列和隐蔽通道发送部分的基本实现（使用x86汇编指令）。需要注意的是：这部分攻击的代码也可以完全用C这样的高级语言来实现。在随后的文章中，我们会讨论列表中的每一行代码是如何完成meltdown攻击的。

Step 1: Reading the secret. To load data from the main memory into a register, the data in the main memory is referenced using a virtual address. In parallel to translating a virtual address into a physical address, the CPU also checks the permission bits of the virtual address, i.e., whether this virtual address is user accessible or only accessible by the kernel. As already discussed in Section 2.2, this hardware-based isolation through a permission bit is considered secure and recommended by the hardware vendors. Hence, modern operating systems always map the entire kernel into the virtual address space of every user process.

步骤1：读内存中的秘密数据。为了将数据从主存储器加载到寄存器中，我们使用虚拟地址来访问主存中的数据。在将虚拟地址转换为物理地址的同时，CPU还会检查虚拟地址的权限位：这个虚拟地址可否被用户态访问，还是只能在内核态中访问。正如在第2.2节中已经讨论过的那样，我们都认为这个基于硬件的地址空间隔离是安全的，并且硬件厂商也推荐使用这种隔离方法。因此，现代操作系统总是将整个内核地址空间映射到每个用户进程的虚拟地址空间。

As a consequence, all kernel addresses lead to a valid physical address when translating them, and the CPU can access the content of such addresses. The only difference to accessing a user space address is that the CPU raises an exception as the current permission level does not allow to access such an address. Hence, the user space cannot simply read the contents of such an address. However, Meltdown exploits the out-of-order execution of modern CPUs, which still executes instructions in the small time window between the illegal memory access and the raising of the exception.

访问内核地址空间的时候，只要创建了虚拟地址的映射（即可以通过页表翻译出一个有效的物理地址），CPU都可以访问这些地址的内容。和访问用户地址空间唯一不同是会进行权限检查，由于当前CPU权限级别不够而访问内核空间地址的时候会触发异常。因此，用户空间不能简单地通过读取内核地址的内容来获得秘密数据。然而，乱序执行的特性允许CPU在一个很小的时间窗口内（从执行了非法内存访问的指令到触发异常），仍然会继续执行指令。Meltdown就是利用了乱序执行的特性完成了攻击。

In line 4 of Listing 2, we load the byte value located at the target kernel address, stored in the RCX register, into the least significant byte of the RAX register represented by AL. As explained in more detail in Section 2.1, the MOV instruction is fetched by the core, decoded into μOPs, allocated, and sent to the reorder buffer. There, architectural registers (e.g., RAX and RCX in Listing 2) are mapped to underlying physical registers enabling out-of-order execution. Trying to utilize the pipeline as much as possible, subsequent instructions (lines 5-7) are already decoded and allocated as μOPs as well. The μOPs are further sent to the reservation station holding the μOPs while they wait to be executed by the corresponding execution unit. The execution of a μOP can be delayed if execution units are already used to their corresponding capacity or operand values have not been calculated yet.

在上面代码列表中的第4行，我们访问了位于内核地址空间的memory（地址保存在RCX寄存器），获取了一个字节的数据，保存在AL寄存器（即RAX寄存器的8个LSB比特）。根据2.1节中的描述，MOV指令由CPU core取指，解码成μOPS，分配并发送到重排序缓冲区。在那里，architectural register（软件可见的寄存器，例如RAX和RCX）会被映射成底层的物理寄存器以便实现乱序执行。为了尽可能地利用流水线，随后的指令（5-7的代码）已经解码并分配为uOPs。该uOPs会进一步送到保留站（暂存uOPs），在保留站中，uOPs会等待相应的执行单元空闲，如果执行单元准备好，该uOPs会立刻执行，如果执行单元已经达到了容量的上限（例如有3个加法器，那么可以同时进行3个加法运算，第四个加法uOPs就需要等待了）或uOPs操作数值尚未计算出来，uOPs则被延迟执行。

When the kernel address is loaded in line 4, it is likely that the CPU already issued the subsequent instructions as part of the out-or-order execution, and that their corresponding μOPs wait in the reservation station for the content of the kernel address to arrive. As soon as the fetched data is observed on the common data bus, the μOPs can begin their execution.

当在程序第4行加载内核地址到寄存器的时候，由于乱序执行，很可能CPU已经把后续指令发射出去，并且它们相应的μOPs会在保留站中等待内核地址的内容到来。一旦在公共数据总线上观察到所获取的内核地址数据，这些μOPs就会立刻开始执行。

When the μOPs finish their execution, they retire in order, and, thus, their results are committed to the architectural state. During the retirement, any interrupts and exception that occurred during the execution of the instruction are handled. Thus, if the MOV instruction that loads the kernel address is retired, the exception is registered and the pipeline is flushed to eliminate all results of subsequent instructions which were executed out of order. However, there is a race condition between raising this exception and our attack step 2 which we describe below.

当μOPs执行完毕后，它们就按顺序进行retire（这个术语叫做retire，很难翻译，这里就不翻译了，但是和commit是一个意思），因此，μOPs的结果会被提交并体现在体系结构状态上。在提交过程中，在执行指令期间发生的任何中断和异常都会被处理。因此，在提交MOV指令的时候发现该指令操作的是内核地址，这时候会触发异常。这时候CPU流水线会执行flush操作，由于乱序执行而提前执行的那些指令（Mov指令之后）结果会被清掉。然而，在触发这个异常和我们执行的攻击步骤2之间有一个竞争条件（race condition），我们在下面描述。

As reported by Gruss et al. [9], prefetching kernel addresses sometimes succeeds. We found that prefetching the kernel address can slightly improve the performance of the attack on some systems.

根据Gruss等人的研究[ 9 ]，预取内核地址有时成功。我们发现：预取内核地址可以略微改善某些系统的攻击性能。

Step 2: Transmitting the secret. The instruction sequence from step 1 which is executed out of order has to be chosen in a way that it becomes a transient instruction sequence. If this transient instruction sequence is executed before the MOV instruction is retired (i.e., raises the exception), and the transient instruction sequence performed computations based on the secret, it can be utilized to transmit the secret to the attacker.

步骤2：传送秘密数据

在步骤1中乱序执行的指令序列能否成为瞬态指令序列是需要条件的。如果的确是瞬态指令序列，那么它必须要在MOV指令retirement之前被执行（即在触发异常之前），而且瞬态指令序列会基于秘密数据进行计算，而这个计算的副作用可以用来向攻击者传递秘密数据。

As already discussed, we utilize cache attacks that allow to build fast and low-noise covert channel using the CPU’s cache. Thus, the transient instruction sequence has to encode the secret into the microarchitectural cache state, similarly to the toy example in Section 3.

正如之前已经讨论过的，我们利用缓存攻击，即利用CPU的高速缓存建立快速和低噪声的隐蔽通道。然后，瞬态指令序列必须要把秘密数据编码在微架构缓存状态中。这个过程类似于第三节中的那个简单示例程序。

We allocate a probe array in memory and ensure that no part of this array is cached. To transmit the secret, the transient instruction sequence contains an indirect memory access to an address which is calculated based on the secret (inaccessible) value. In line 5 of Listing 2 the secret value from step 1 is multiplied by the page size, i.e., 4 KB. The multiplication of the secret ensures that accesses to the array have a large spatial distance to each other. This prevents the hardware prefetcher from loading adjacent memory locations into the cache as well. Here, we read a single byte at once, hence our probe array is 256×4096 bytes, assuming 4KB pages.

我们在内存中分配一个探测数组，并确保该数组的所有内存都没有被cached。为了传递秘密数据，瞬态指令序列包含对探测数组的间接内存访问，具体的访问地址是基于那个秘密数据的（该秘密数据是用户态不可访问的）。具体可以参考上面列表中的第5行代码：第1步获取的秘密数据会乘以页面大小，即4 KB（代码使用了移位操作，是一样的意思）。这个乘法操作确保了对数组的访问具有较大的空间距离。这可以防止硬件prefetcher把相邻存储单元的数据加载到缓存中。在这示例中，由于一次只读出一个字节，所以我们的探测数组是256×4096字节（假设页面大小是4KB）。

Note that in the out-of-order execution we have a noise-bias towards register value ‘0’. We discuss the reasons for this in Section 5.2. However, for this reason, we introduce a retry-logic into the transient instruction sequence. In case we read a ‘0’, we try to read the secret again (step 1). In line 7, the multiplied secret is added to the base address of the probe array, forming the target address of the covert channel. This address is read to cache the corresponding cache line. Consequently, our transient instruction sequence affects the cache state based on the secret value that was read in step 1.

注意：在乱序执行中，我们对寄存器值“0”有一个噪声偏置（noise-bias）。我们在第5.2节讨论了具体的原因。正是由于这个原因，我们在瞬态指令序列中引入了重试逻辑。如果我们读到了“0”值，我们试着重新读这个秘密数据（第1步）。在代码的第7行中，将秘密数据乘以4096并累加到探测数组的基地址中，从而形成隐蔽信道的目标地址。读取该目标地址可以将数据加载到对应的cacheline中。因此，瞬态指令序列根据第1步中读取的秘密数据修改了探测数组对应的缓存状态。

Since the transient instruction sequence in step 2 races against raising the exception, reducing the runtime of step 2 can significantly improve the performance of the attack. For instance, taking care that the address translation for the probe array is cached in the TLB increases the attack performance on some systems.

由于步骤2中的瞬态指令序列需要和异常的触发相竞争，因此减少步骤2的运行时间可以显著提高攻击的性能。例如：把探测数组的地址翻译预先缓存在TLB中。

Step 3: Receiving the secret. In step 3, the attacker recovers the secret value (step 1) by leveraging a microarchitectural side-channel attack (i.e., the receiving end of a microarchitectural covert channel) that transfers the cache state (step 2) back into an architectural state. As discussed in Section 4.2, Meltdown relies on Flush+Reload to transfer the cache state into an architectural state.

步骤3：接收秘密数据。

在步骤3中，攻击者利用微架构侧信道攻击（即微架构隐蔽信道的接收端）将cache state转换成了软件可以感知的体系结构状态（architectural state），从而恢复了秘密数据。正如第4.2节中所讨论的，meltdown依赖于Flush+Reload来将缓存状态转换为CPU体系结构状态。

When the transient instruction sequence of step 2 is executed, exactly one cache line of the probe array is cached. The position of the cached cache line within the probe array depends only on the secret which is read in step 1. Thus, the attacker iterates over all 256 pages of the probe array and measures the access time for every first cache line (i.e., offset) on the page. The number of the page containing the cached cache line corresponds directly to the secret value.

在步骤2中执行的瞬态指令序列时，整个探测数组只有一个页面的cacheline被加载了。具体加载的cacheline的在探测数组中的位置仅取决于步骤1中读取的秘密数据。因此，攻击者遍历所有探测数组中的256个页面，测试每个页面第一个cacheline的访问时间，已经预先加载了cacheline的那个page index就直接对应着秘密数据的数值。

Dumping the entire physical memory. By repeating all 3 steps of Meltdown, the attacker can dump the entire memory by iterating over all different addresses. However, as the memory access to the kernel address raises an exception that terminates the program, we use one of the methods described in Section 4.1 to handle or suppress the exception.

Dump整个物理内存：

通过重复上面的3个步骤，同时修改不同的攻击地址，攻击者可以dump所有内存。但是，由于对内核地址的内存访问引发了一个终止程序的异常，所以我们使用第4.1节中描述的方法来处理或抑制这个异常。

As all major operating systems also typically map the entire physical memory into the kernel address space (cf. Section 2.2) in every user process, Meltdown is not only limited to reading kernel memory but it is capable of reading the entire physical memory of the target machine.

在目前所有的主流操作系统中，我们通常会把整个物理内存映射到内核地址空间（参见第2.2节），而每个用户进程中又包括内核地址空间部分。因此Meltdown不仅能读取内核地址空间的内存值，而且能够读取整个系统的物理内存。

2、优化和限制（optimizations and limitations）

The case of 0. If the exception is triggered while trying to read from an inaccessible kernel address, the register where the data should be stored, appears to be zeroed out. This is reasonable because if the exception is unhandled, the user space application is terminated, and the value from the inaccessible kernel address could be observed in the register contents stored in the core dump of the crashed process. The direct solution to fix this problem is to zero out the corresponding registers. If the zeroing out of the register is faster than the execution of the subsequent instruction (line 5 in Listing 2), the attacker may read a false value in the third step. To prevent the transient instruction sequence from continuing with a wrong value, i.e., ‘0’, Meltdown retries reading the address until it encounters a value different from ‘0’ (line 6). As the transient instruction sequence terminates after the exception is raised, there is no cache access if the secret value is 0. Thus, Meltdown assumes that the secret value is indeed ‘0’ if there is no cache hit at all.

读出数值是0的场景。

根据前面的描述，在instruction commit阶段，当检测到用户态访问内核地址的时候，除了触发异常，CPU还会清除指令的操作结果，也就是说AL寄存器会被清零。如果瞬态指令序列在和异常的竞争中失败了（寄存器清零早于上面程序列表中第五行代码执行），那么很可能从内核地址读出的并非其真是值，而是清零后的数值。对寄存器清零也是合理的，因为如果异常没有被处理，用户空间的应用程序会终止，该进程的core dump文件中会保留寄存器的内容，如果不清零，那么内核空间的数据可以通过core dump文件泄露出去。清零可以修正这个issue，保证内核空间数据的安全。为了防止瞬态指令序列继续操作错误的“0”值，Meltdown会重读地址直到读出非“0”值（第6行代码）。

你可能会问：如果秘密数据就是0怎么办？其实当异常触发后，瞬态指令序列终止执行，如果秘密数据确实等于0，则不存在任何cacheline被加载。因此，meltdown在进行探测数据cacheline扫描过程中，如果没有任何cacheline命中，那么秘密数据实际上就是“0”。

The loop is terminated by either the read value not being ‘0’ or by the raised exception of the invalid memory access. Note that this loop does not slow down the attack measurably, since, in either case, the processor runs ahead of the illegal memory access, regardless of whether ahead is a loop or ahead is a linear control flow. In either case, the time until the control flow returned from exception handling or exception suppression remains the same with and without this loop. Thus, capturing read ‘0’s beforehand and recovering early from a lost race condition vastly increases the reading speed.

无论是读出数值非“0”或无效地址访问触发了异常，代码中的循环逻辑都会终止。注意，这个循环不会降低攻击的性能，因为，在上面两种情况中，CPU会提前允许非法内存访问指令之后的代码指令，而CPU并不关心这些指令是一个循环控制或是一个线性的控制流。无论哪一种情况，从异常处理函数（或者异常抑制）返回的时间都是一样的，和有没有循环控制是无关的。因此，尽早发现读出值是“0”，也就是说尽早发现自己在和异常的竞争中失败并恢复，可以大大提高了读取速度。

Single-bit transmission ：

In the attack description in Section 5.1, the attacker transmitted 8 bits through the covert channel at once and performed 28 = 256 Flush+Reload measurements to recover the secret. However, there is a clear trade-off between running more transient instruction sequences and performing more Flush+Reload measurements. The attacker could transmit an arbitrary number of bits in a single transmission through the covert channel, by either reading more bits using a MOV instruction for a larger data value. Furthermore, the attacker could mask bits using additional instructions in the transient instruction sequence. We found the number of additional instructions in the transient instruction sequence to have a negligible influence on the performance of the attack.

单个bit数据的发送：

在第5.1节的描述中，攻击者通过隐蔽通道一次可以传输8个bit，接收端执行2^8＝256 次Flush+Reload命令来恢复秘密数据。不过，我们需要在运行更多的瞬态指令序列和执行更多的Flush+Reload测量之间进行平衡。攻击者可以通过隐蔽通道在一次传输中发送任意比特的数据，当然这需要使用MOV指令去读取更多bit的秘密数据。此外，攻击者可以在瞬态指令序列中增加mask的操作（这样可以传送更少的bit，从而减少接收端Flush+Reload的次数）。我们发现在瞬态指令序列中增加的指令数对攻击的性能影响是微不足道的。

The performance bottleneck in the generic attack description above is indeed, the time spent on Flush+Reload measurements. In fact, with this implementation, almost the entire time will be spent on Flush+Reload measurements. By transmitting only a single bit, we can omit all but one Flush+Reload measurement, i.e., the measurement on cache line 1. If the transmitted bit was a ‘1’, then we observe a cache hit on cache line 1. Otherwise, we observe no cache hit on cache line 1.

上面描述的meltdown攻击中的性能瓶颈主要是在通过Flush+Reload恢复秘密数据上所花费的时间。实际上在本章中的meltdown代码实现中，几乎所有的时间都将花费在Flush+Reload上了。如果只发送一个bit，那么除了一次Flush+Reload测量时间，其他的我们都可以忽略。在这种情况下，我们只需要检测一个cacheline的状态，如果cache hit，那么传输的bit是“1”，如果cache miss，那么传输的bit是“0”。

Transmitting only a single bit at once also has drawbacks. As described above, our side channel has a bias towards a secret value of ‘0’. If we read and transmit multiple bits at once, the likelihood that all bits are ‘0’ may quite small for actual user data. The likelihood that a single bit is ‘0’ is typically close to 50 %. Hence, the number of bits read and transmitted at once is a tradeoff between some implicit error-reduction and the overall transmission rate of the covert channel.

一次只传输一个比特也有缺点。如上所述，我们的侧通道更偏向于“0”值。如果我们一次读取多个比特的秘密数据并发送出去，那么所有bit都是“0”的可能性应该说是相当小。单个bit等于“0”的可能性通常接近50%。因此，一次传输的比特数是需要在隐蔽信道的总传输速率和减少差错之间进行平衡。

However, since the error rates are quite small in either case, our evaluation (cf. Section 6) is based on the single-bit transmission mechanics.

不过，由于两种情况下的错误率都很小，因此我们的评估（参见第6节）是基于单比特传输机制的。

Exception Suppression using Intel TSX.

和Intel的TSX相关，暂时没有兴趣了解。

Dealing with KASLR.

In 2013, kernel address space layout randomization (KASLR) had been introduced to the Linux kernel (starting from version 3.14 [4]) allowing to randomize the location of the kernel code at boot time. However, only as recently as May 2017, KASLR had been enabled by default in version 4.12 [27]. With KASLR also the direct-physical map is randomized and, thus, not fixed at a certain address such that the attacker is required to obtain the randomized offset before mounting the Meltdown attack. However, the randomization is limited to 40 bit.

处理KASLR。

2013年，内核地址空间布局随机化（KASLR）已被合并到Linux内核中（从3.14版开始[ 4 ]），这个特性允许在开机的时候把内核代码加载到一个随机化地址上去。在最近的（2017年5月）4.12版的内核中，KASLR已经被默认启用[ 27 ]。并且直接映射部分的地址也是随机的，并非固定在某个地址上。因此，在利用meltdown漏洞对内核进行攻击之前，攻击者需要需要获得一个40-bit的随机偏移值。

Thus, if we assume a setup of the target machine with 8GB of RAM, it is sufficient to test the address space for addresses in 8GB steps. This allows to cover the search space of 40 bit with only 128 tests in the worst case. If the attacker can successfully obtain a value from a tested address, the attacker can proceed dumping the entire memory from that location. This allows to mount Meltdown on a system despite being protected by KASLR within seconds.

假设目标机有8GB内存，那么我们其实是可以使用8G的步长来进行地址空间的探测。即便是在最坏的情况下也只有128次就可以确定这个40-bit的随机偏移值。攻击者一旦能够成功地攻击某个测试地址，那么他也可以继续从该位置dump整个内存。尽管系统受到KASLR的保护，实际上利用meltdown漏洞，攻击者也可以在几秒钟内完成攻击。

六、评估（Evaluation）

In this section, we evaluate Meltdown and the performance of our proof-of-concept implementation 2. Section 6.1 discusses the information which Meltdown can leak, and Section 6.2 evaluates the performance of Meltdown, including countermeasures. Finally, we discuss limitations for AMD and ARM in Section 6.4.

在本章中，我们将评估meltdown的影响以及我们POC（proof-of-concept）实现的性能。6.1节讨论了meltdown可能泄漏的信息，6.2节评估了meltdown的性能和对策。最后在6.4节中，我们讨论了在AMD和ARM处理器上meltdown的局限性。

Table 1 shows a list of configurations on which we successfully reproduced Meltdown. For the evaluation of Meltdown, we used both laptops as well as desktop PCs with Intel Core CPUs. For the cloud setup, we tested Meltdown in virtual machines running on Intel Xeon CPUs hosted in the Amazon Elastic Compute Cloud as well as on DigitalOcean. Note that for ethical reasons we did not use Meltdown on addresses referring to physical memory of other tenants.

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在上面列表显示的系统中，我们都成功地利用meltdown漏洞进行了攻击。我们在使用英特尔CPU的笔记本电脑和台式机上进行了meltdown的评估。对于云服务器，我们测试Amazon Elastic Compute Cloud和DigitalOcean的虚拟机，CPU是英特尔的Xeon处理器。出于道德的原因，我们没有使用meltdown去获取真实用户物理内存地址上的数据。

1、各种环境下的信息泄露（Information Leakage and Environments）

We evaluated Meltdown on both Linux (cf. Section 6.1.1) and Windows 10 (cf. Section 6.1.3). On both operating systems, Meltdown can successfully leak kernel memory. Furthermore, we also evaluated the effect of the KAISER patches on Meltdown on Linux, to show that KAISER prevents the leakage of kernel memory (cf. Section 6.1.2). Finally, we discuss the information leakage when running inside containers such as Docker (cf. Section 6.1.4).

我们在Linux（参见第6.1.1）和Windows 10（参见第6.1.3）这两个操作系统上评估了meltdown漏洞，结果表明它们都可以成功地泄漏内核信息。此外，我们还测试了KAISER补丁在Linux上的效果，结果表明KAISER补丁可以防止内核信息泄漏（参见第6.1.2）。最后，我们讨论了在容器环境下（例如Docker）的信息泄漏（参见第6.1.4）。

（1）Linux

We successfully evaluated Meltdown on multiple versions of the Linux kernel, from 2.6.32 to 4.13.0. On all these versions of the Linux kernel, the kernel address space is also mapped into the user address space. Thus, all kernel addresses are also mapped into the address space of user space applications, but any access is prevented due to the permission settings for these addresses. As Meltdown bypasses these permission settings, an attacker can leak the complete kernel memory if the virtual address of the kernel base is known. Since all major operating systems also map the entire physical memory into the kernel address space (cf. Section 2.2), all physical memory can also be read.

我们成功地对多个版本的Linux内核（从2.6.32到4.13.0）进行了Meltdown评估。在Linux内核的所有这些版本中，内核地址空间都映射到了用户进程地址空间中。但由于权限设置，任何来自用户空间的内核数据访问都被阻止。Meltdown可以绕过这些权限设置，并且只要攻击者知道内核虚拟地址，都可以发起攻击，从而泄露内核数据。由于所有主要操作系统都将整个物理内存映射到内核地址空间（参见第2.2节），因此利用meltdown漏洞可以读取所有物理内存的数据。

Before kernel 4.12, kernel address space layout randomization (KASLR) was not active by default [30]. If KASLR is active, Meltdown can still be used to find the kernel by searching through the address space (cf. Section 5.2). An attacker can also simply de-randomize the direct-physical map by iterating through the virtual address space. Without KASLR, the direct-physical map starts at address 0xffff 8800 0000 0000 and linearly maps the entire physical memory. On such systems, an attacker can use Meltdown to dump the entire physical memory, simply by reading from virtual addresses starting at 0xffff 8800 0000 0000.

在4.12内核之前，内核地址空间布局随机化（KASLR）不是默认启用的[ 30 ]。如果启动KASLR这个特性，meltdown仍然可以用来找到内核的映射位置（这是通过搜索地址空间的方法，具体参见5.2节）。攻击者也可以通过遍历虚拟地址空间的方法来找到物理内存直接映射的信息。没有KASLR，Linux内核会在0xffff 8800 0000 0000开始的线性地址区域内映射整个物理内存。在这样的系统中，攻击者可以用meltdown轻松dump整个物理内存，因为攻击者已经清楚的知道物理内存的虚拟地址是从0xffff 8800 0000 0000开始的。

On newer systems, where KASLR is active by default, the randomization of the direct-physical map is limited to 40 bit. It is even further limited due to the linearity of the mapping. Assuming that the target system has at least 8GB of physical memory, the attacker can test addresses in steps of 8 GB, resulting in a maximum of 128 memory locations to test. Starting from one discovered location, the attacker can again dump the entire physical memory.

在新的linux系统中，KASLR是默认启动的，因此物理内存的虚拟地址并非从0xffff 8800 0000 0000开始，而是需要累加一个40-bit的随机偏移。由于物理内存的映射是线性的，KASLR阻挡meltdown攻击的效果进一步受到限制。假设目标系统有8GB内存，攻击者可以按照8 GB的步长来破解40-bit的随机偏移，最多128次尝试就可以推出这个随机偏移。一旦攻破了随机偏移值，攻击者可以再次dump整个物理内存。

Hence, for the evaluation, we can assume that the randomization is either disabled, or the offset was already retrieved in a pre-computation step.

因此，在本节的meltdown评估中，我们可以假设KASLR是禁用的，或者随机偏移量已经在预先计算出来了。

（2）打了KAISER补丁的Linux系统（Linux with KAISER patch）

The KAISER patch by Gruss et al. [8] implements a stronger isolation between kernel and user space.

KAISER does not map any kernel memory in the user space, except for some parts required by the x86 architecture (e.g., interrupt handlers). Thus, there is no valid mapping to either kernel memory or physical memory (via the direct-physical map) in the user space, and such addresses can therefore not be resolved. Consequently, Meltdown cannot leak any kernel or physical memory except for the few memory locations which have to be mapped in user space.

Gruss发布的KAISER补丁[ 8 ]实现了内核和用户空间之间更强的隔离。KAISER根本不把内核地址空间映射到用户进程空间中去。除了x86架构所需的某些部分代码之外（如中断处理程序），在用户空间中根本看不到物理内存的直接映射，也看不到内核地址空间的任何信息。没有有效的映射，因此用户空间根本不能解析这些地址。因此，除了少数必须在用户空间中映射的物理内存或者内核地址外，meltdown不能泄漏任何数据。

We verified that KAISER indeed prevents Meltdown, and there is no leakage of any kernel or physical memory.

我们验证了KAISER确实解决了meltdown漏洞，没有任何内核或物理内存数据的泄漏。

Furthermore, if KASLR is active, and the few remaining memory locations are randomized, finding these memory locations is not trivial due to their small size of several kilobytes. Section 7.2 discusses the implications of these mapped memory locations from a security perspective.

此外，如果启用了KASLR，虽然有部分内核地址空间的映射是用户态可见的，但是这些内核地址的位置是随机的，而且由于这段内存区域只有几KB，发现这些内存位置不是一件简单的事情。7.2节从安全的角度讨论了映射这一小段内存的含义。

（3）Windows

没有兴趣了解，略过。

（4）容器

We evaluated Meltdown running in containers sharing a kernel, including Docker, LXC, and OpenVZ, and found that the attack can be mounted without any restrictions. Running Meltdown inside a container allows to leak information not only from the underlying kernel, but also from all other containers running on the same physical host.

我们评估了容器环境下（共享一个内核）的meltdown，包括Docker，LXC，和OpenVZ，结果发现meltdown可以没有任何限制发起攻击。在容器中运行执行meltdown攻击不仅可以泄漏底层内核信息，还可以泄漏同一物理主机上其他容器上的信息。

The commonality of most container solutions is that every container uses the same kernel, i.e., the kernel is shared among all containers. Thus, every container has a valid mapping of the entire physical memory through the direct-physical map of the shared kernel. Furthermore, Meltdown cannot be blocked in containers, as it uses only memory accesses. Especially with Intel TSX, only unprivileged instructions are executed without even trapping into the kernel.

大多数容器解决方案都是使用相同的内核，即内核是在所有容器中共享的。因此，每个容器中都有对整个物理内存的直接映射。由于只涉及内存访问，在容器中并不能阻止meltdown攻击。特别是在使用英特尔TSX特性的情况下，攻击根本不需要陷入内核执行，只有非特权指令的执行。

Thus, the isolation of containers sharing a kernel can be fully broken using Meltdown. This is especially critical for cheaper hosting providers where users are not separated through fully virtualized machines, but only through containers. We verified that our attack works in such a setup, by successfully leaking memory contents from a container of a different user under our control.

因此，共享内核的容器隔离可以轻松地被meltdown攻破。对于那些提供廉价主机托管服务的提供商来说，这个问题更严重，因为在那种情况下，用户不能通过完全虚拟化的物理机器进行隔离，而只能通过容器进行隔离。我们验证了在这样的环境中，meltdown的确是起作用的，我们可以成功地从其他用户容器中盗取内存信息。

2、meltdown性能

To evaluate the performance of Meltdown, we leaked known values from kernel memory. This allows us to not only determine how fast an attacker can leak memory, but also the error rate, i.e., how many byte errors to expect. We achieved average reading rates of up to 503KB/s with an error rate as low as 0.02% when using exception suppression. For the performance evaluation, we focused on the Intel Core i7-6700K as it supports Intel TSX, to get a fair performance comparison between exception handling and exception suppression.

为了评估meltdown的性能，我们事先在准备攻击的内核内存中设定了指定的数值。这使我们不仅能够确定攻击者盗取内存数据的速度，而且还可以确定错误率（即有多少字节的错误）。在使用异常抑制（需要TSX支持）的情况下，我们实现了503kB / s的数据泄露速度，而错误率低于0.02%。对于性能评估，我们集中在英特尔的Core i7-6700k处理器，因为它支持TSX。这样我们可以在一个公平环境中（同一个CPU）比较异常处理和异常抑制两种方法下meltdown的性能。

For all tests, we use Flush+Reload as a covert channel to leak the memory as described in Section 5. We evaluated the performance of both exception handling and exception suppression (cf. Section 4.1). For exception handling, we used signal handlers, and if the CPU supported it, we also used exception suppression using Intel TSX. An extensive evaluation of exception suppression using conditional branches was done by Kocher et al. [19] and is thus omitted in this paper for the sake of brevity.

对于所有的测试，我们使用Flush+Reload作为一个隐蔽通道来泄漏内存信息，具体可以参考第5章的描述。我们评估了异常处理和异常抑制这两种方法下meltdown的性能（参见第4.1节）。对于异常处理，我们设置信号处理函数。如果CPU支持，我们也可以利用英特尔TSX来完成异常抑制。使用条件分支来完成异常抑制的评估是由Kocher等人完成的[ 19 ]。为了简洁起见，本文省略了这部分的内容。

（1）异常处理

Exception handling is the more universal implementation, as it does not depend on any CPU extension and can thus be used without any restrictions. The only requirement for exception handling is operating system support to catch segmentation faults and continue operation afterwards. This is the case for all modern operating systems, even though the specific implementation differs between the operating systems. On Linux, we used signals, whereas, on Windows, we relied on the Structured Exception Handler.

异常处理的方法更通用一些，因为它不依赖于任何CPU扩展特性，从而可以不受任何限制地在各种处理器上使用。异常处理的唯一要求是操作系统支持捕捉segmentation fault并继续操作。基本上所有现代操作系统都支持这个特性，不过具体的实现会有所不同。在Linux上，我们使用信号，而在Windows上，我们依赖Structured Exception Handler。

With exception handling, we achieved average reading speeds of 123KB/s when leaking 12MB of kernel memory. Out of the 12MB kernel data, only 0.03%were read incorrectly. Thus, with an error rate of 0.03 %, the channel capacity is 122KB/s.

在使用异常处理的情况下，我们实现了以123kB / s的平均速度完成了12MB内核数据的泄漏。在12MB的内核数据中，错误率只有0.03%。因此信道容量是122kB／s。

（2）异常抑制

和Intel处理器相关，忽略之。

3、Meltdown实战

这个小节展示了几个具体的meltdown攻击效果，忽略之。

4、AMD和ARM处理器上的限制

We also tried to reproduce the Meltdown bug on several ARM and AMD CPUs. However, we did not manage to successfully leak kernel memory with the attack described in Section 5, neither on ARM nor on AMD. The reasons for this can be manifold. First of all, our implementation might simply be too slow and a more optimized version might succeed. For instance, a more shallow out-of-order execution pipeline could tip the race condition towards against the data leakage. Similarly, if the processor lacks certain features, e.g., no re-order buffer, our current implementation might not be able to leak data. However, for both ARM and AMD, the toy example as described in Section 3 works reliably, indicating that out-of-order execution generally occurs and instructions past illegal memory accesses are also performed.

我们还试图在几款ARM和AMD CPU上重现meltdown漏洞。然而无论是在ARM上还是在AMD处理器上，我们都没有成功地使用第5章中描述的攻击方法来盗取到内核内存。造成这种情况的原因是多方面的。首先，我们的实现可能太慢，一个更优化的版本可能会成功。例如，一个更浅的乱序执行流水线可能会让数据泄漏变得更困难一些。类似地，如果处理器缺少某些特性，例如没有重新排序缓冲区（re-order buffer），那么我们当前的代码实现可能根据无法造成泄漏数据。不过，对于ARM和AMD处理器来说，第3章中描述的简单示例仍然可以可靠的工作，这表明在那些CPU上也发生了乱序执行，即非法内存访问的指令之后的指令也提前被执行。

七、对策

In this section, we discuss countermeasures against the Meltdown attack. At first, as the issue is rooted in the hardware itself, we want to discuss possible microcode updates and general changes in the hardware design. Second, we want to discuss the KAISER countermeasure that has been developed to mitigate side-channel attacks against KASLR which inadvertently also protects against Meltdown.

在这一章中，我们讨论了如何应对meltdown攻击。由于这个issue本身是源于硬件设计，因此我们首先讨论如何通过更新硬件设计来修复这个漏洞。其次，我们讨论如何用KAISER来减轻meltdown，虽然KAISER最初的设计是为了防止KASLR侧信道攻击的。

1、硬件策略

Meltdown bypasses the hardware-enforced isolation of security domains. There is no software vulnerability involved in Meltdown. Hence any software patch (e.g., KAISER [8]) will leave small amounts of memory exposed (cf. Section 7.2). There is no documentation whether such a fix requires the development of completely new hardware, or can be fixed using a microcode update.

Meltdown并不涉及软件漏洞，它是直接绕过硬件隔离机制。因此，任何软件补丁（例如，KAISER[8]）都会暴露出少量的内存区域（参见第7.2节）。是否需要开发全新的硬件或使用微码更新来修复meltdown，没有文件说明这一点。

As Meltdown exploits out-of-order execution, a trivial countermeasure would be to completely disable out-of-order execution. However, the performance impacts would be devastating, as the parallelism of modern CPUs could not be leveraged anymore. Thus, this is not a viable solution.

由于meltdown利用了乱序执行，一个简单的对策就是完全禁用乱序执行。不过这对性能的影响将是毁灭性的，因为我们将无法再利用现代CPU的并行性了。因此，这个解决方案不可行。

Meltdown is some form of race condition between the fetch of a memory address and the corresponding permission check for this address. Serializing the permission check and the register fetch can prevent Meltdown, as the memory address is never fetched if the permission check fails. However, this involves a significant overhead to every memory fetch, as the memory fetch has to stall until the permission check is completed.

Meltdown是“获取内存地址数据”和“权限检查”之间的一种竞态条件（race condition）。严格在获取地址数据之前进行权限检查可以防止meltdown，即在不能通过权限检查时候，CPU根本没有办法把受保护的内存数据加载到寄存器。然而，这给每一个内存访问增加了很大的开销，因为在完成权限检查之前，内存访问的动作只能stall。

A more realistic solution would be to introduce a hard split of user space and kernel space. This could be enabled optionally by modern kernels using a new hard split bit in a CPU control register, e.g., CR4. If the hard split bit is set, the kernel has to reside in the upper half of the address space, and the user space has to reside in the lower half of the address space. With this hard split, a memory fetch can immediately identify whether such a fetch of the destination would violate a security boundary, as the privilege level can be directly derived from the virtual address without any further lookups. We expect the performance impacts of such a solution to be minimal. Furthermore, the backwards compatibility is ensured, since the hard-split bit is not set by default and the kernel only sets it if it supports the hard-split feature.

一个更现实的解决方案是从硬件层面区分用户空间和内核空间。这可以通过CPU寄存器（例如cr4）的一个bit（称之hard-split bit）来开启。如果该bit设置为1，则内核地址必须在地址空间的上半部分，而用户空间必须位于地址空间的下半部分。有了这种硬件机制，违反权限的内存读取可以被立刻识别，这是因为所需特权级别可以直接从虚拟地址推导出来而不需要任何进一步的查找。我们认为这种解决方案对性能的影响是最小的。此外，向后兼容性也得到保证，因为默认情况下我们不设置hard-split bit，而内核仅在硬件支持的时候才设置它。

Note that these countermeasures only prevent Meltdown, and not the class of Spectre attacks described by Kocher et al. [19]. Likewise, several countermeasures presented by Kocher et al. [19] have no effect on Meltdown. We stress that it is important to deploy countermeasures against both attacks.

请注意，这些对策只能防止meltdown，对Kocher等人发现的幽灵攻击无效[ 19 ]。同样，由Kocher等人提出的解决spectre漏洞[ 19 ] 的对策，对meltdown也没有效果。我们这里再次强调一下：针对这两种攻击部署相关的对策是非常重要的。

2、KAISER

As hardware is not as easy to patch, there is a need for software workarounds until new hardware can be deployed. Gruss et al. [8] proposed KAISER, a kernel modification to not have the kernel mapped in the user space. This modification was intended to prevent side-channel attacks breaking KASLR [13, 9, 17]. However, it also prevents Meltdown, as it ensures that there is no valid mapping to kernel space or physical memory available in user space. KAISER will be available in the upcoming releases of the Linux kernel under the name kernel page-table isolation (KPTI) [25]. The patch will also be backported to older Linux kernel versions. A similar patch was also introduced in Microsoft Windows 10 Build 17035 [15]. Also, Mac OS X and iOS have similar features [22].

硬件修复漏洞没有那么快，因此我们还是要到在新的硬件可以部署之前，提供软件绕过的方案。Gruss等人[ 8 ]建议了KAISER方案，该方案对内核进行修改，以便在用户进程地址空间中根本看不到内核地址的映射。这个补丁是为了防止侧信道攻击方法攻破KASLR [ 13, 9, 17 ]。然而，因为它确保了在用户空间没有有效的内核空间映射或物理内存映射，因此KAISER也能解决meltdown问题。KAISER将会出现在即将发布的Linux内核中，名字改成了KPTI（kernel page-table isolation）[ 25 ]，同时该补丁也将移植到旧的Linux内核版本。微软Windows 10也提供了类似的补丁[ 15 ]。另外，Mac OS X和iOS也有类似的功能[ 22 ]。

Although KAISER provides basic protection against Meltdown, it still has some limitations. Due to the design of the x86 architecture, several privileged memory locations are required to be mapped in user space [8]. This leaves a residual attack surface for Meltdown, i.e., these memory locations can still be read from user space. Even though these memory locations do not contain any secrets, such as credentials, they might still contain pointers. Leaking one pointer can be enough to again break KASLR, as the randomization can be calculated from the pointer value.

虽然KAISER提供了基本的保护以防止meltdown，但它仍然有一些局限性。由于x86架构的设计，需要在用户空间中映射一小段内核地址空间[ 8 ]，因此这些内存位置仍然可以从用户空间读取，这为meltdown攻击留下伏笔。即使这些内存位置不包含任何机密数据，它们仍然可能包含指针。其实一个指针的数据就足够攻破KASLR，因为随机偏移可以根据指针的值推导出来。

Still, KAISER is the best short-time solution currently available and should therefore be deployed on all systems immediately. Even with Meltdown, KAISER can avoid having any kernel pointers on memory locations that are mapped in the user space which would leak information about the randomized offsets. This would require trampoline locations for every kernel pointer, i.e., the interrupt handler would not call into kernel code directly, but through a trampoline function. The trampoline function must only be mapped in the kernel. It must be randomized with a different offset than the remaining kernel. Consequently, an attacker can only leak pointers to the trampoline code, but not the randomized offsets of the remaining kernel. Such trampoline code is required for every kernel memory that still has to be mapped in user space and contains kernel addresses. This approach is a trade-off between performance and security which has to be assessed in future work.

不过，KAISER仍然是目前最好的短期解决方案，并且应该立即部署到所有系统上。即便是CPU存在meltdown漏洞，KAISER补丁避免了在用户空间映射的内存位置上保存内核的指针，这样可以避免泄露随机偏移的信息。为了达到这个目标，我们需要为每一个内核指针建立trampoline code，例如：中断处理程序不会直接调用内核代码，而是通过trampoline函数。trampoline函数只会映射到内核空间，但是和其余部分的内核应该在不同的随机偏移上。因此，攻击者只能获取trampoline code的内核地址，而不能破解剩余内核的随机偏移。每一个进程地址空间仍然映射了trampoline code这段内存，而这段内存中也包括了内核的地址，存在一定的风险，但是这种方法是性能和安全性之间进行平衡，也是我们必须在今后的工作进一步研究的课题。

八、讨论

Meltdown fundamentally changes our perspective on the security of hardware optimizations that manipulate the state of microarchitectural elements. The fact that hardware optimizations can change the state of microarchitectural elements, and thereby imperil secure soft-ware implementations, is known since more than 20 years [20]. Both industry and the scientific community so far accepted this as a necessary evil for efficient computing. Today it is considered a bug when a cryptographic algorithm is not protected against the microarchitectural leakage introduced by the hardware optimizations. Meltdown changes the situation entirely. Meltdown shifts the granularity from a comparably low spatial and temporal granularity, e.g., 64-bytes every few hundred cycles for cache attacks, to an arbitrary granularity, allowing an attacker to read every single bit. This is nothing any (cryptographic) algorithm can protect itself against. KAISER is a short-term software fix, but the problem we uncovered is much more significant.

通过调整CPU微架构状态，CPU设计者可以优化硬件的性能，由此引入的安全问题并没有引起足够的重视，Meltdown从根本上改变了这一点，即CPU设计者必须直面安全问题。20多年以来，CPU设计者很清楚的知道这样一个事实：硬件优化可以改变CPU微架构的状态，从而给安全软件的实现带来风险[ 20 ]。但是到目前为止，工业界和科学界都认为这是高效计算所必需面对的一个问题，你不得不接受它。现在，当一个加密算法不能保护微架构状态的泄露（由于硬件优化而引入），我们认为这是一个软件bug。Meltdown彻底改变了现状。原来的攻击在空间和时间粒度上是相对较小，例如，缓存攻击的空间粒度是64个字节，时间粒度是大概几百个周期。有了meltdown，空间和时间粒度可以任意指定，允许攻击者读取每一个比特位，这不是什么（加密）算法可以保护了的。KAISER是一个短期的软件解决方案，但我们揭示的问题更为重要（即不能为了性能而忽略安全性）。

We expect several more performance optimizations in modern CPUs which affect the microarchitectural state in some way, not even necessarily through the cache. Thus, hardware which is designed to provide certain security guarantees, e.g., CPUs running untrusted code, require a redesign to avoid Meltdown- and Spectre-like attacks. Meltdown also shows that even error-free software, which is explicitly written to thwart side-channel attacks, is not secure if the design of the underlying hardware is not taken into account.

我们期待更多的性能优化出现在现代CPU上，这些优化可能以某种方式影响微架构的状态（未必一定是影响缓存状态，可能是其他的CPU微架构单元）。不过只要CPU硬件的设计需求中包含了安全性，那么CPU设计者就需要重新设计以避免meltdown和spectre的攻击。Meltdown还表明：即便是软件没有bug，而且也小心的设计以避免侧信道攻击，如果不仔细思考底层硬件的安全性，那么它也是不安全的。

With the integration of KAISER into all major operating systems, an important step has already been done to prevent Meltdown. KAISER is also the first step of a paradigm change in operating systems. Instead of always mapping everything into the address space, mapping only the minimally required memory locations appears to be a first step in reducing the attack surface. However, it might not be enough, and an even stronger isolation may be required. In this case, we can trade flexibility for performance and security, by e.g., forcing a certain virtual memory layout for every operating system. As most modern operating system already use basically the same memory layout, this might be a promising approach.

随着KAISER集成到目前所有的主流操作系统中，我们在防止meltdown上已经迈出了重要的一步。KAISER也改变了操作系统中地址映射的设计思路。原来我们总是将所有地址（包括内核和用户）映射到整个进程地址空间，现在，在用户态执行的时候只是映射必要的地址空间。这的确是减少攻击范围。然而，这可能是不够的，我们可能需要更强烈的隔离。在这种情况下，我们需要在性能和安全性上进行平衡，例如，强制每个操作系统符合特定的虚拟内存布局。由于大多数现代操作系统使用了基本相同的内存布局，这可能是一种很有前途的方法。

Meltdown also heavily affects cloud providers, especially if the guests are not fully virtualized. For performance reasons, many hosting or cloud providers do not have an abstraction layer for virtual memory. In such environments, which typically use containers, such as Docker or OpenVZ, the kernel is shared among all guests. Thus, the isolation between guests can simply be circumvented with Meltdown, fully exposing the data of all other guests on the same host. For these providers, changing their infrastructure to full virtualization or using software workarounds such as KAISER would both increase the costs significantly.

Meltdown也严重影响了云服务提供商，特别是在客户机没有完全虚拟化的场景中。出于性能方面的原因，许多云服务提供商没有虚拟内存的抽象层。在这样的环境中（通常是使用容器，如Docker或OpenVZ），内核在所有的guest os中共享。因此，虽然存在guest os之间的隔离，但是我们可以利用Meltdown，将其他guest os的数据（在同一个主机）暴露出来。对于这些供应商，改变他们的基础设施，变成全虚拟化或使用软件解决方法（如KAISER）都会增加成本。

Even if Meltdown is fixed, Spectre [19] will remain an issue. Spectre [19] and Meltdown need different defenses. Specifically mitigating only one of them will leave the security of the entire system at risk. We expect that Meltdown and Spectre open a new field of research to investigate in what extent performance optimizations change the microarchitectural state, how this state can be translated into an architectural state, and how such attacks can be prevented.

即使meltdown被修复了，spectre[ 19 ]仍然是一个问题。Spectre和meltdown需要不同的防御策略。只是解决其中一个并不能解决整个系统的安全问题。我们期待meltdown和spectre可以打开一个新的研究领域，让大家一起探讨CPU设计的相关问题，包括改变微架构的状态如何可以优化CPU性能，微架构状态如何转化为CPU体系结构状态，以及如何阻止这样的攻击。

九、结论

In this paper, we presented Meltdown, a novel softwarebased side-channel attack exploiting out-of-order execution on modern processors to read arbitrary kernel- and physical-memory locations from an unprivileged user space program. Without requiring any software vulnerability and independent of the operating system, Meltdown enables an adversary to read sensitive data of other processes or virtual machines in the cloud with up to 503KB/s, affecting millions of devices. We showed that the countermeasure KAISER [8], originally proposed to protect from side-channel attacks against KASLR, inadvertently impedes Meltdown as well. We stress that KAISER needs to be deployed on every operating system as a short-term workaround, until Meltdown is fixed in hardware, to prevent large-scale exploitation of Meltdown.

在本文中，我们描述了一个新型的CPU漏洞meltdown，一种利用现代处理器上的乱序执行特性，通过侧信道攻击读取任意内核地址和物理内存数据的方法。不需要利用软件漏洞，也和具体操作系统无关，利用Meltdown漏洞，普通用户空间程序可以以503KB／s的速度读其他进程或虚拟机的敏感数据，这影响了数以百万计的设备。我们发现针对meltdown的对策是KAISER [ 8 ]，KAISER最初是为了防止侧信道攻击KASLR而引入的，但是无意中也可以防止meltdown漏洞。我们建议：一个短期的解决办法是在每一个操作系统上都部署KAISER，直到解决meltdown issue的硬件出现。

十、致谢

We would like to thank Anders Fogh for fruitful discussions at BlackHat USA 2016 and BlackHat Europe 2016, which ultimately led to the discovery of Meltdown. Fogh [5] already suspected that it might be possible to abuse speculative execution in order to read kernel memory in user mode but his experiments were not successful. We would also like to thank Jann Horn for comments on an early draft. Jann disclosed the issue to Intel in June. The subsequent activity around the KAISER patch was the reason we started investigating this issue. Furthermore, we would like Intel, ARM, Qualcomm, and Microsoft for feedback on an early draft.

我们感谢Anders Fogh在BlackHat USA 2016和BlackHat Europe 2016上富有成果的讨论，这些讨论最终导致meltdown的发现。Anders Fogh [ 5 ]已经怀疑利用推测执行可以在用户模式下读取内核数据，但他的实验并不成功。我们也要感谢Jann Horn对早期草稿的意见。Jann Horn在6月份向Intel透漏了这个问题。随后围绕KAISER补丁的后续活动也使得我们开始调查这个问题。此外，我们也欣赏英特尔、ARM、高通和微软在早期草案阶段给予的反馈。

We would also like to thank Intel for awarding us with a bug bounty for the responsible disclosure process, and their professional handling of this issue through communicating a clear timeline and connecting all involved researchers. Furthermore, we would also thank ARM for their fast response upon disclosing the issue.

我们也要感谢英特尔公司，在发现meltdown漏洞之后对我们进行了奖励，并且负责的披露整个过程，感谢他们专业的处理了这个问题（给出一个明确的时间表进行充分沟通，并联系了所有相关的研究人员）。此外，我们还感谢ARM在披露问题时的快速反应。

This work was supported in part by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 681402).

欧洲研究委员会（ERC）根据欧盟Horizon 2020科研创新计划（编号：681402）对本项工作有一定的支持。

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