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title: Exploiting and Protecting Dynamic Code Generation
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resource: "https://www.ndss-symposium.org/ndss2015/ndss-2015-programme/exploiting-and-protecting-dynamic-code-generation/"
title: Exploiting and Protecting Dynamic Code Generation
author: Chengyu Song, Chao Zhang, Tielei Wang, Wenke Lee, David Melski
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authors:
- Chengyu Song
- Chao Zhang
- Tielei Wang
- Wenke Lee
- David Melski
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# Exploiting and Protecting Dynamic Code Generation
**Exploiting and Protecting Dynamic Code Generation** - Chengyu Song, Chao Zhang, Tielei Wang, Wenke Lee, David Melski, NDSS Symposium.
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Exploiting and Protecting Dynamic Code Generation
Chengyu Song Chao Zhang Tielei Wang, Wenke Lee David Melski
Georgia Institute of Technology UC Berkeley Georgia Institute of Technology GrammaTech
csong84@gatech.edu chaoz@berkeley.edu tielei.wang@gmail.com, melski@grammatech.com
wenke@cc.gatech.edu
Abstract—Many mechanisms have been proposed and de- effective. DEP is a subset of the more general security policy
ployed to prevent exploits against software vulnerabilities. Among W⊕X, which enforces that memory should either be writable
them, W⊕X is one of the most effective and efficient. W⊕X but not executable (e.g., data segments), or be executable
prevents memory pages from being simultaneously writable but read-only (e.g., code segments). This enforcement can
and executable, rendering the decades old shellcode injection completely mitigate traditional exploits that inject malicious
technique infeasible.
shellcode into data segments. Consequently, attackers have to
In this paper, we demonstrate that the traditional shellcode leverage more complicated exploit techniques, such as return-
injection attack can be revived through a code cache injection to-libc [53] and return-oriented-programming (ROP) [52].
technique. Specifically, dynamic code generation, a technique Moreover, W⊕X memory has become the foundation of many
widely used in just-in-time (JIT) compilation and dynamic binary other protection techniques, such as control flow integrity
translation (DBT), generates and modifies code on the fly in order (CFI) [2, 63, 64].
to promote performance or security. The dynamically generated
code fragments are stored in a code cache, which is writable However, the effectiveness of W⊕X can be undermined
and executable either at the same time or alternately, resulting by another important compilation technique – dynamic code
in an opportunity for exploitation. This threat is especially generation (DCG). With the ability to generate and execute
realistic when the generated code is multi-threaded, because native machine code at runtime, DCG is widely used in just-
switching between writable and executable leaves a time window in-time (JIT) compilers [7] and dynamic binary translators
for exploitation. To illustrate this threat, we have crafted a proof-
of-concept exploit against modern browsers that support Web
(DBT) [28, 48] to improve performance, portability, and secu-
Workers. rity. For example, JIT compilers for dynamic languages (e.g.,
JavaScript and ActionScript) can leverage platform information
To mitigate this code cache injection threat, we propose a and runtime execution profile information to generate faster
new dynamic code generation architecture. This new architecture native code. DBTs can leverage DCG to provide dynamic
relocates the dynamic code generator to a separate process, analysis capability [28], cross-platform or cross-architecture
in which the code cache is writable. In the original process
portability [9, 47], bug diagnostics [33, 45], and enhanced
where the generated code executes, the code cache remains read-
only. The code cache is synchronized across the writing process security [8, 12, 25, 26, 36].
and the execution process through shared memory. Interaction A fundamental challenge posed by DCG is that the code
between the code generator and the generated code is handled cache, in which the dynamically generated code is stored,
transparently through remote procedure calls (RPC). We have
needs to be both writable (for code emitting, code patching,
ported the Google V8 JavaScript engine and the Strata DBT
to this new architecture. Our implementation experience showed and garbage collection) and executable. This violates the W⊕X
that the engineering effort for porting to this new architecture policy and enables a new attack vector. We have observed
is minimal. Evaluation of our prototype implementation showed a real world exploit that delivers shellcode into the writable
that this new architecture can defeat the code cache injection code cache and successfully compromises the Chrome web
attack with small performance overhead. browser [43].
Solving this problem seems trivial. A straightforward idea,
I. I NTRODUCTION which has been adopted in browsers like mobile Safari, is
demonstrated in Figure 1. This technique keeps the code cache
Exploits against software vulnerabilities remain one of the
as read-only and executable (RX) when the generated code is
most severe threats to cyber security. To mitigate this threat,
executing; switches to writable but not executable (WR) when
many techniques have been proposed, including data execution
it needs to be modified (t1); and switches back to RX when
prevention (DEP) [4] and address space layout randomization
the write operation finishes (t2). As a result, the code cache
(ASLR) [42], both of which have been widely deployed and are
will remain read-only when the generated code is executing;
and the attack demonstrated in [43] can be mitigated.
Permission to freely reproduce all or part of this paper for noncommercial
purposes is granted provided that copies bear this notice and the full citation
Unfortunately, in addition to performance overhead, this
on the first page. Reproduction for commercial purposes is strictly prohibited simple mechanism does not work well with multi-threaded
without the prior written consent of the Internet Society, the first-named author programs. First, if the code generator uses a shared code cache
(for reproduction of an entire paper only), and the author’s employer if the for all threads (e.g., PIN [28]), then the code cache cannot be
paper was prepared within the scope of employment. switched to WR, because other concurrently running threads
NDSS ’15, 8-11 February 2015, San Diego, CA, USA
Copyright 2015 Internet Society, ISBN 1-891562-38-X require the executable permission. Second, even if the code
http://dx.doi.org/10.14722/ndss.2015.23233 generator uses a dedicated code cache for each thread (e.g., JS
engines), the protection is still flawed and is subject to race and around 1.64% for SPEC CINT 2006 (additional to Strata’s
condition attacks [34], as shown in Figure 2. More specifically, own overhead).
memory access permissions are applied to the whole process
In summary, we made the following contributions:
and are shared among all threads. When one thread turns on the
writable permission for its code cache (e.g., for code emitting), • Beyond known exploit techniques against permanently
the code cache also becomes writable to all other threads. Once writable code cache [43], we demonstrated the feasibility
the write permission is set, another concurrently running thread of exploiting race conditions to maliciously modify code
can (maliciously) overwrite the first thread’s code cache to cache protected by permission switching based W⊕X
launch attacks. This is similar to the classic time-of-check- enforcement; and discussed the severity of such attacks
to-time-of-use (TOCTTOU) problem [29], where the resource (Section III).
to be accessed is modified between the check and the use by • We proposed secure dynamic code generation (SDCG), a
exploiting race conditions. multi-process-based architecture that provides better secu-
rity (mandatory, non-bypassible W⊕X enforcement), low
In this paper, we demonstrate the feasibility of such race-
performance overhead, and easy adoption (Section IV).
condition-based code cache injection attacks, through a proof-
• We implemented two prototypes of SDCG, one for V8
of-concept exploit against modern browsers that support the
JS engine and one for Strata dynamic binary translator
Web Worker [57] specification. Rather than relying on a per-
(Section V).
manently writable code cache [43], our attack leverages race
• We evaluated the performance overhead of our two pro-
conditions and can bypass permission-switching-based W⊕X
totype implementations (Section VI).
enforcement (Figure 1). In this attack, the malicious JS code
utilizes web workers to create a multi-threaded environment.
After forcing a worker thread into the compilation state, the II. R ELATED W ORK
main JS thread can exploit vulnerabilities of the browser to In this section, we discuss the techniques that could be
inject shellcode into the worker thread’s code cache. used to protect a code cache from being maliciously modified
and explain their disadvantages. We also discuss other forms
To fundamentally prevent such attacks, we propose secure
of attacks against the JIT engines and their countermeasures.
dynamic code generation (SDCG), a new architecture that 1)
enables dynamic code generation to comply with the W⊕X
policy; 2) eliminates the described race condition; 3) can be A. Software-based Fault Isolation
easily adopted; and 4) introduces less performance overhead Software-based fault isolation (SFI) [58] can be used to
compared to alternative solutions. SDCG achieves these goals confine a program’s ability to access memory resources. On
through a multi-process-based architecture. Specifically, in- 32-bit x86 platforms, SFI implementations usually leverage
stead of generating and modifying code in a single process, segment registers [20, 62] to confine memory accesses for
SDCG relocates the DCG functionality to a second trusted the benefit of low runtime overhead. On other platforms
process. The code cache is built upon memory shared between without segment support (e.g., x86-64, ARM), SFI implemen-
the original process and the trusted process. In the original tations use either address masking [49] or access control lists
process, the code cache is mapped as RX; and in the trusted (ACL) [10], introducing higher runtime overhead.
process, the same memory is mapped as WR. By doing so,
the code cache remains read-only under all circumstances Once memory accesses — especially write accesses — are
in the untrusted process, eliminating the race condition that confined, SFI can prevent untrusted code from overwriting
allows the code cache to be writable to untrusted thread(s). security sensitive data, such as the code cache. Our SDCG
At the same time, the code generator in the trusted process solution differs from SFI in several respects. First, SFI’s
can freely perform code generation, patching and garbage overhead comes from the execution of the extra inline checks;
collection as usual. To enable transparent interaction between SDCG’s overhead comes from remote procedure calls and
the code generator and the generated code, we only need to cache synchronization on multi-core systems. Therefore, if
add a few wrappers that make the code generator invocable execution stays mostly within the code cache, SDCG will
through remote procedure calls (RPC). Since only functions introduce less overhead than SFI. On the other hand, if
that modify code cache need to be handled, the effort for execution needs to be frequently switched between the code
adding wrappers is small. generator and the generated code, then SFI could be faster.
Since most modern code generators try to make the execution
We implemented SDCG for two types of popular code stay as long as possible in the code cache, our approach is
generators: JS engine and DBT. For JS engine, our implemen- more suitable in most cases.
tation is based on V8 [24]. For DBT, our implementation is
Second, to reduce the overhead of address masking, many
based on Strata [48]. Our implementation experience showed
SFI solutions [49] use ILP32 (32-bit integer, long, pointer)
that porting code generators to SDCG only requires a small
primitive data types, limiting data access to 4GB of space,
modification: besides the shareable part, which is about 500
even on a 64-bit platform. SDCG does not have this limitation.
lines of C code (LoC), we only added about 2,500 LoC
for V8 and about 1,000 LoC for Strata. We evaluated the It is worth noting that some efforts have been made to
security of SDCG and the performance overhead of our two apply SFI to JIT engines [5, 38]. Despite relatively higher
prototype implementations. The results showed that SDCG is overhead, the threat model of these approaches usually did not
secure under our threat model and the performance overhead consider scenarios where the JIT compiler is only a component
introduced by our prototype implementations is small: around of a larger software solution, such as a web browser. Since
6.90% (32-bit) and 5.65% (64-bit) for V8 benchmark suite; most web browser vulnerabilities are found outside the JIT
2
Code Cache (RX) Code Cache (WR) Code Cache (RX)
Thread
Code Generator Running
t1 t2 Generated Code Running
Fig. 1: A permission switching based W⊕X enforcement. The code cache is kept as read-only when the generated code is
executing. When the code generator is invoked (t1), the permission is changed to writable; and when the generator finishes its
task (t2), the permission is changed back to read-only.
Code Cache (RX) Code Cache (WR) Code Cache (RX)
Thread A 1 2 3 4
Thread B
Code Generator Running
t1 t2 Generated Code Running
Fig. 2: Race-condition-based attack using two threads. With switching based W⊕X enforcement, a single thread (A) can no
longer attack the code cache (access 1), but the code cache can still be attacked using multiple threads. When the code generator
is serving one thread (access 2), the code cache will also become writable for other threads (access 3). The attack window is t2
- t1. Once the code generator finishes its task, the code cache becomes read-only again (access 4).
engines [17], to apply such techniques one would have to apply a program’s control flow cannot be hijacked to unexpected
SFI to other browser components as well. This could result in locations. CFI could protect the code cache in some way,
even higher performance overhead. From this perspective, we e.g., attackers cannot overwrite the code cache by jumping
argue that our solution is more realistic in practice. to arbitrary addresses of the code generator.
B. Memory Safety However, attackers can still utilize arbitrary memory write
vulnerabilities to overwrite the code cache without break-
Attacks on code caches (at randomized locations) rely ing CFI. Once the code cache is overwritten, injected code
on the ability to write to a memory area specified by an could be invoked through normal function invocations, without
attacker. Therefore, such attacks could be defeated by memory breaking the static CFI policy.
safety enforcement, which prevents all unexpected memory
reads and writes. However, many programs are written in Moreover, when extending CFI to dynamically generated
low-level languages like C/C++, and are prone to memory code, without proper write protection the embedded enforce-
corruption bugs, leading to the majority of security vulner- ment checks can also be removed once attackers can overwrite
abilities for these languages. Unfortunately, existing memory the code. From this perspective, SDCG is complementary to
safety solutions [6, 19, 31, 32, 41, 51, 61] for C/C++ programs CFI because it guarantees one basic assumption of CFI: code
tend to have much higher performance overhead than SFI or integrity protection.
other solutions, prohibiting their adoptions. For example, the
combination of Softbound [31] and CETS [32] provides a
strong spatial and temporal memory safety guarantee, but they
were reported to have 116% average overhead on SPEC CPU D. Process Sandbox
2000 benchmark. Compared with this direction of research,
even though SDCG provides less security guarantees, it is still A delegation-based sandbox architecture, a.k.a. the broker
valuable because it fully blocks a powerful attack vector with model [21], has been widely adopted by the industry and used
minimal runtime overhead. in Google Chrome [23], Windows 8 [30], Adobe Reader [3],
etc. In this architecture, the sandboxed process drops most of
its privileges and delegates all security sensitive operations to
C. Control Flow Integrity
the broker process. The broker process then checks whether the
Control flow hijacking is a key step in many real world request complies with the security policy. SDCG is based on
attacks. As DEP becomes ubiquitous, more and more attacks the same architecture. Using this architecture, we 1) delegate
rely on return-to-libc [53] or ROP [52] to hijack control all the operations that will modify the code cache (e.g., code
flow. Many solutions [2, 63, 64] have been proposed to installation, patching, and deletion) to the translator process;
enforce control flow integrity (CFI) policy. With CFI policy, and 2) make sure the W⊕X policy is mandatory.
3
E. Attacks on JIT engines • Address Space Layout Randomization. We assume that
the target system has at least deployed base address ran-
Attackers have targeted the code cache for its writable domization, and all predictable memory mappings have
and executable properties. Currently, the most popular exploit been eliminated.
technique is JIT spray [54], an extension to classic heap spray • JIT Spray Mitigation. For JIT engines, we assume that
attacks [18]. Heap spray is used to bypass ASLR without they implement a full-suite of JIT spray mitigation mecha-
guessing the address of injected shellcode. This technique nisms, including but not limited to random NOP insertion,
becomes unreliable after DEP is deployed because the heap constant splitting, and those proposed in [5, 60].
is no longer executable. To bypass this, attackers turned to • Guard Pages. We assume the target system creates guard
JIT engines. The JIT spray attack abuses the JIT engine to pages (i.e., pages without access permission) to wrap each
emit chunks of predictable code, and then hijacks control flow pool of the code cache, as seen in the Google V8 JS
toward the entry or middle of one of these code chunks. DEP engine. These guard pages can prevent buffer overflows,
or W⊕X is thus bypassed because these code chunks reside both overflows out of the code cache, and overflows into
in the executable code cache. Most JIT engines have since the code cache.
deployed different mitigation techniques to make the layout • Page Permissions. We assume that the underlying hard-
of the code cache unpredictable, e.g., random NOP insertion, ware has support for mapping memory as non-executable
constant splitting, etc. Researchers have also proposed more (NX), and that writable data memory like the stack and
robust techniques [5, 60] to prevent such attacks. normal heap are set to be non-executable. Furthermore,
Rather than abusing JIT engines to create expected code, we assume that all statically generated code has been set
attackers can also abuse the writable property of the code cache to non-writable to prevent overwriting. However, almost
and directly overwrite generated code [43]. In the next section, all JIT compilers map the code cache as both writable
we first extend this attack to show that even with a permission and executable.
switching based W⊕X enforcement, attackers can still leverage The target system can further deploy the following ad-
race conditions to bypass such enforcement. vanced mitigation mechanisms for the purpose of sandboxing
and monitoring:
III. ATTACKING THE C ODE C ACHE • Fine-grained Randomization. The target system can en-
In this section, we describe in detail the code cache force fine-grained randomization by permuting the order
injection threat we are addressing in this paper. We begin this of functions [27] or basic blocks [59], randomizing the
section with our assumptions and threat model. Next, we show location of each instruction [39], or even randomizing the
how the code cache can be attacked to bypass state-of-the-art instruction set [8].
exploit mitigation techniques. Finally, we demonstrate how a • Control Flow Hijacking Mitigation. The target system can
naive W⊕X enforcement can be bypassed by exploiting race deploy control flow hijacking mitigation mechanisms, in-
conditions. cluding (but not limited to): control flow integrity enforce-
ment, either coarse-grained [63, 64] or fine-grained [2,
37]; return-oriented programming detection [13, 40]; and
A. Assumptions and Threat Model dynamic taint analysis based hijacking detection [36].
SDCG focuses on preventing remote attackers from leverag- To allow overwriting of the code cache, we assume
ing the code cache as an attack vector to achieve arbitrary code there is at least one vulnerability that allows attackers to
execution. We focus on two classic attack scenarios discussed write to an attacker-specified address with attacker-provided
as follows. In both scenarios, we assume the code generator contents. We believe this is a realistic assumption, because
itself is trusted and does not have security vulnerabilities. many types of vulnerabilities can be exploited to achieve this
goal, such as format string [35], heap overflow [16], use-
• Foreign Attacks. In this scenario, the code generator is after-free [14], integer overflow [15], etc. For example, the
a component of a program (e.g., a web browser). The attack described in [43] obtained this capability by exploiting
program is benign, but components other than the code an integer overflow vulnerability (CVE-2013-6632); in [11],
generator are assumed to be vulnerable when handling the author described how five use-after-free vulnerabilities
input or contents provided by an attacker (e.g., a malicious (CVE-2013-0640, CVE-2013-0634, CVE-2013-3163, CVE-
web page). Attackers can then exploit the vulnerable 2013-1690, CVE-2013-1493) can be exploited to perform
components to attack the code cache. arbitrary memory writes. It is worth noting that in many attack
• Jailbreak Attacks. In this scenario, the code generator is scenarios, the ability to do arbitrary memory write can easily
used to sandbox or monitor an untrusted program, and lead to arbitrary memory read and information disclosure
attacks are launched within the code cache. This could abilities.
happen under two circumstances. First, the sandboxed
program itself is malicious. Second, the program is be- B. Overwriting the Code Cache to Bypass Exploit Mitigation
nign, but the dynamically generated code has vulnerabil- Techniques
ities that can be exploited by attackers to jailbreak.
1) Software Dynamic Translator: For ease of discussion,
Without loss of generality, we assume that the following we use the term software dynamic translator (SDT) to represent
mitigation mechanisms for both general and JIT-based exploits software that leverages dynamic code generation to translate
have been deployed on the target system. code in one format to another format. Before describing the
4
attacks, we first give a brief introduction on SDT. A core task 4) Security Implication: In practice, we have only observed
of all SDTs is to maintain a mapping between untranslated this single attack that injects code into the code cache. We
code and translated code. Whenever a SDT encounters a new believe this is mainly due to the convenience of a popular
execution unit (depending on the SDT, the execution unit could ROP attack pattern, which works by: i) preparing traditional
be a basic block, a function, or a larger chunk of code), it shellcode in memory; ii) exploiting vulnerabilities to launch an
first checks whether the execution unit has been previously ROP attack; iii) using the ROP gadgets to turn on the execution
translated. If so, it begins executing the translated code residing permission of memory where the traditional shellcode resides;
in the code cache; otherwise, it translates this new execution and iv) jumping to the traditional shellcode to finish the
unit and installs the translated code into the code cache. intended malicious tasks. However, once advanced control flow
hijacking prevention mechanisms such as fine-grained CFI are
2) Exploit Primitives: In this section, we describe how the
deployed, this attack pattern will be much more difficult to
code cache with full WRX permission can be overwritten. This
launch.
is done in two steps. First, we need to bypass ASLR and find
out where the code cache is located. Second, we need to write The code cache injection attack can easily bypass most of
to the identified location. the existing exploit mitigation mechanisms. First, all control
flow hijacking detection/prevention mechanisms such as CFI
a) Bypassing ASLR: The effectiveness of ASLR or
and ROP detection rely on the assumption that the code
any randomization based mitigation mechanism relies on two
cannot be modified. When this assumption is broken, these
assumptions: i) the entropy is large enough to stop brute-force
mitigation mechanisms are no longer effective. Second, any
attacks; and ii) the adversary cannot learn the random value
inline reference monitor based security solution is not effective
(e.g., module base, instruction set).
because the injected code is not monitored.
Unfortunately, these two assumptions rarely hold in prac-
tice. First, on 32-bit platforms, user space programs only C. Exploiting Race Conditions to Bypass W⊕X Enforcement
have 8 bits of entropy for heap memory, which is subject
to brute-force guessing [53] and spray attacks [18]. Second, A naive defense against the code cache injection attack is
with widely available information disclosure vulnerabilities, to enforce W⊕X by manipulating page permissions (Figure 1).
attackers can easily recover the random value [46, 50]. In fact, More specifically, when the code cache is about to be modified
researchers have demonstrated that even with a single restricted (e.g., for new code generation or runtime garbage collection),
information disclosure vulnerability, it is possible to traverse the code generator turns on the write permission and turns off
a large portion of memory content [55]. the execution permission (t1). When the code cache is about
to be executed, the generator turns off the write permission
When attacking a code cache, we can either launch a and turns on the execution permission (t2).
JIT spray attack to prepare a large number of WRX pages
on platforms with low entropy, or leverage an information This solution prohibits the code cache to be both writable
disclosure vulnerability to pinpoint the location of the code and executable at the same time. If the target program is
cache. Note that as one only needs to know the location of single-threaded, this approach can prevent code cache injection
the code cache, most fine-grained randomizations that try to attacks. Since the code cache is only writable when the SDT
further randomize the contents of memory are ineffective for is executing and we assume that the SDT itself is trusted and
this attack. Since the content of code cache will be overwritten not vulnerable, attackers cannot hijack or interrupt the SDT to
in the next step (described below), none of the JIT spray overwrite the code cache. However, as illustrated in Figure 2, in
mitigation mechanisms can provide effective protection against a more general multi-threaded programming environment, even
this attack. if the SDT is trusted, the code cache can still be overwritten
by other insecure threads when the the code cache is set to be
b) Writing to the Code Cache: The next step is to inject writable for one thread.
shellcode to the code cache. In most cases, the code cache will
not be adjacent to other writable heap memory (due to ASLR), In this section, we use a concrete attack to demonstrate the
and may also be surrounded by guard pages. For these reasons, feasibility of such attacks, i.e., with naive W⊕X enforcement,
we cannot directly exploit a buffer overflow vulnerability to it is still possible to overwrite the code cache with the same
overwrite the code cache. However, as our assumption section exploit primitives described above.
suggests, besides logic errors that directly allow one to write 1) Secure Page Permissions: Since the V8 JS engine does
to anywhere in memory, several kinds of memory corruption not have the expected page permission protection, i.e., the
vulnerabilities can also provide arbitrary memory write ability. naive W⊕X enforcement, we implemented this naive protec-
In the following example, an integer overflow vulnerability is tion in V8 to demonstrate of our attack.
exploited to acquire this capability.
By default, when a memory region is allocated from the OS
3) An In-the-Wild Attack: We have observed one disclosed (e.g., via mmap) for the code cache, it is allocated as executable
attack [43] that leveraged the code cache to achieve reliable ar- but not writable. We will turn on the write permission and turn
bitrary code execution. This attack targeted the mobile Chrome off the execution permission of the code cache for:
browser. By exploiting an integer overflow vulnerability, the
attack first gained reliable arbitrary memory read and write • New Code Installation. Usually, the JavaScript program
capabilities. Using these two capabilities, the attack subse- (e.g., a function) is first compiled into native code, and
quently bypassed ASLR and located the permanently writable then copied into the code cache. To allow the copy
and executable code cache. Finally, it injected shellcode into operation, we need to turn on the write permission of
the code cache and turned control flow to the shellcode. the code cache.
5
• Code Patching. Existing code in the code cache is patched Since synchronization is an essential part of multi-
under certain circumstances. For instance, after new code threaded programming, almost all SDTs support thread
is copied into the code cache, its address is thus deter- synchronization. In JS, thread synchronization uses the
mined; instructions that require address operands from postMessage function.
this new code fragment are resolved and patched.
• Runtime Inline Caching. Inline caching is a special patch- 3) A Proof-of-Concept Attack: Based on the vulnerability
ing mechanism introduced to provide better performance disclosed in the previous real-world exploit, we built a proof-
for JIT-compiled programs written in dynamically typed of-concept race-condition-based attack on the Chrome browser.
languages. With runtime execution profile information, Since the disclosed attack [43] already demonstrated how
the JIT compiler caches/patches the result (e.g., the result ASLR can be bypassed and how arbitrary memory write
of object property resolving) into instructions in the code capability can be acquired, our attack focuses on how race
cache at runtime. conditions can be exploited to bypass naive W⊕X enforce-
• Runtime Garbage Collection. The JavaScript engine needs ment. The high level workflow of our attack is as follows:
to manage the target JavaScript program’s memory via
garbage collection. This will require the code cache to i) Create a Worker. The main JS thread creates a web worker,
be modified for two main reasons. First, when an unused and thus a worker thread is created.
code fragment needs to be removed; and second, when ii) Initialize the Worker. The worker thread initializes its
a data object is moved to a new address by the garbage environment, making sure the code cache is created.
collector, instructions referencing it have to be updated. It then sends a message to the main thread through
postMessage that it is ready.
When these operations finish, or any code in the code cache iii) Locate the Worker’s Code Cache. Upon receiving the
needs to be invoked, we turn off the write permission of the worker’s message, the main JS thread locates the worker
code cache and turn on the execution permission. thread’s code cache, e.g., by exploiting an information
disclosure vulnerability. In the Chrome V8 engine, at-
To further reduce the attack surface, all of the above tackers can locate the code cache using the previously
policies are enforced with fine-grained granularity. That is, disclosed exploit. Instead of following the pointers for the
1) each permission change only covers memory pages that current thread, attackers should go through the thread list
are accessed by the write or execution operations; and 2) the the JS engine maintains and follow pointers for the worker
write permission is turned on only when a write operation thread. Then, the main thread informs the worker that it
is performed, and is turned off immediately after the write is ready.
operation finishes. This fine-grained implementation provides iv) Make the Code Cache Writable. Upon receiving the main
maximum protection for code caches. thread’s message, the worker thread begins to execute
another piece of code, forcing the SDT to update its
2) Multi-threaded Programming in SDT: To launch the
code cache. In V8, the worker can execute a function
race-condition-based attack, we need two more programming
that is large enough to force the SDT to create a new
primitives. First, we need the ability to write multi-threaded
MemoryChunk for the code fragment and set it to be
programs. Note that some SDTs such as Adobe Flash Player
writable (for a short time).
also allows “multi-threaded” programming, but each “thread”
v) Monitor and Overwrite the Code Cache. At the same time,
is implemented as a standalone OS process. For these SDTs,
the main thread monitors the status of the code cache
since the code cache is only writable to the corresponding
and tries to overwrite it once its status is updated. In
thread, our proposed exploit technique would not work. Sec-
V8, the main thread can keep polling the head of the
ond, since the attack window is generally small, we need the
MemoryChunk linked list to identify the creation of a
ability to coordinate threads before launching the attack.
new code fragment. Once a new code fragment is created,
• Thread Primitives. A majority of SDTs have multi- the main thread can then monitor its content. Once the first
threaded programming support. JavaScript (JS) used to be few bytes (e.g., the function prologue) are updated, the
single-threaded and event-driven. With the new HTML5 main thread can try to overwrite the code cache to inject
specification, JS also supports multi-threaded program- shellcode. After overwriting, the main thread informs the
ming through the WebWorker specification [57]. There worker it has finished.
are two types of WebWorker: dedicated worker and vi) Execute the Shellcode. Upon receiving the main thread’s
shared worker. In V8, the dedicated worker is imple- new message, the worker calls the function whose content
mented as a thread within the same process; a shared has already been overwritten. In this way, the injected
worker is implemented as a thread in a separate process. shellcode is executed.
Since we want to attack one JS thread’s code cache with It is worth noting that the roles of the main thread and the
another JS thread, we leverage the dedicated worker. Note worker thread cannot be swapped in practice, because worker
that although each worker thread has its own code cache, threads do not have access to the document object model
it is still possible to launch the attack, because memory (DOM). Since many vulnerabilities exist within the rendering
access permissions are shared by all threads in the same engine rather than the JS engine, this means only the main
process. thread (which has the access to the DOM) can exploit those
• Synchronization Primitives. To exploit the race condition, vulnerabilities.
two attacker-controlled threads need to synchronize their
operations so that the overwrite can happen within the 4) Reliability of the Race Condition: One important ques-
exact time window when the code cache is writable. tion for any race-condition-based attack is its reliability. The
6
first factor that can affect the reliability of our attack is safety to a large, complex program (e.g., a web browser) would
synchronization, i.e., the synchronization primitive should be be very high. Second, implementing the first choice requires
fast enough so that the two threads can carry out the attack significant engineering effort.
within the relatively small attack window. To measure the
speed of the synchronization between the worker and the main
thread, we ran another simple experiment:
i) The main thread creates a worker thread;
ii) The worker thread gets a timestamp and sends it to the
main thread;
iii) Upon receiving the message, the main thread sends an
echo to the worker;
iv) Upon receiving the message, the worker thread sends back
an echo;
v) The main thread and the worker repeatedly send echoes
to each other 1,000 times.
vi) The main thread obtains another timestamp and computes
the time difference.
The result shows that the average synchronization delay is
around 23 µs. The average attack window (t2−t1 in Figure 2)
of our fine-grained naive W⊕X protection is about 43 µs. Thus,
in theory, the postMessage method is sufficiently fast to Fig. 3: Overview of SDCG’s multi-process-based architecture.
launch a race condition attack. The gray memory areas are shared memory, others are mapped
as private (copy-on-write). Depending on the requirement, the
The second and more important factor that can affect the SDT’s code and data can be mapped differently.
reliability of our attack is task scheduling. Specifically, if the
thread under the SDT context (e.g., the worker thread) is de-
scheduled by the OS while the attacking thread (e.g., the main
thread) is executing, then the attack window will be increased. Figure 3 shows the high level design of SDCG. The key
The only way to change the code cache’s memory permission idea is that through shared memory, the same memory content
is through a system call, and a context switch is likely to will be mapped into two (or more) different processes, with
happen during the system call. For example, the system call for different access permissions. In the untrusted process(es), the
changing memory access permissions on Linux is mprotect. code cache will be mapped as RX; but in the SDT process,
During the invocation of mprotect, since we are using fine- it will be mapped as WR. By doing so, SDCG prevents any
grained protection, the virtual memory area needs to be split untrusted code from modifying the code cache. At the same
or merged. This will trigger the thread to be de-scheduled. As time, it allows the SDT to modify the code cache as usual.
a result, the main thread (with higher priority than the worker) Whenever the SDT needs to be invoked (e.g., to install a new
can gain control to launch attacks. code fragment), the request will be served through a remote
procedure call (RPC) instead of a normal function call.
Considering these two factors, we tested our attack against
the Chrome browser 100 times. Of these 100 tests, 91 suc- To build and maintain this memory model, we need to solve
ceeded. following technical and engineering challenges. the
IV. S YSTEM D ESIGN i) Memory Map Synchronization. Since the memory regions
In this section, we present the design of SDCG. We have occupied by the code cache are dynamically allocated and
two design goals: 1) SDCG should prevent all possible code can grow and shrink freely, we need an effective way
injection attacks against the code cache under our adversary to dynamically synchronize memory mapping between
model; and 2) SDCG should introduce acceptable performance the untrusted process(es) and the SDT process. More
overhead. In addition, SDCG is designed to be integrated with importantly, to make SDCG’s protection mechanism work
the targeted SDT, and we assume that the source code of the transparently, we have to make sure that the memory
SDT is available. is mapped at exactly the same virtual address in all
processes.
ii) Remote Procedure Call. After relocating the SDT to
A. Overview and Challenges another process, we need to make it remotely invocable by
Since the root cause of the attack is a writable code wrapping former local invocations with RPC stubs. Since
cache (either permanently or temporarily), we can prevent RPC is expensive, we need to reduce the frequency of
such attacks making one of two design choices: 1) ensure invocations, which also reduces the attack surface.
that nothing but the SDT can write to the code cache, e.g., iii) Permission Enforcement. Since SDCG’s protection is based
through SFI or memory safety; and 2) ensure that the memory on memory access permissions, we must make sure that
occupied by the code cache is always mapped as RX. We untrusted code cannot tamper with our permission scheme.
selected the second option for two reasons. First, we expect Specifically, memory content can be mapped as either
that the performance overhead of applying SFI or memory writable or executable, but never both at the same time.
7
B. Memory Map Synchronization To avoid this problem, SDCG takes a more systematic ap-
proach. Specifically, based on the observation that a majority of
Synchronizing memory mapping between the untrusted
data that the SDT depends on is either read-only or resides in
process(es) and the SDT process is a bi-directional issue. On
dynamically mapped memory, we extend the shared memory to
one hand, when the SDT allocates a new code fragment in the
also include the dynamic data the SDT depends on. According
SDT process, we should map the same memory region in the
to the required security guarantee, the data should be mapped
untrusted process(es) at exactly the same address; otherwise
with different permissions. By default, SDCG maps the SDT’s
the translated code will not work correctly (e.g., create an
dynamic data as read-only in the untrusted process, to prevent
incorrect branching target). On the other hand, the untrusted
tampering by the untrusted code. However, if non-control data
process may also allocate some resources that are critical to
attacks are not considered, the SDT’s dynamic data can be
the SDT. For example, in the scenario of binary translation,
mapped as WR in the untrusted process. After sharing the data,
when the untrusted process loads a dynamically linked module,
we only need to handle a few cases where writable data (e.g.,
we should also load the same module at the same address
pointers within global variables) is not shared/synchronized.
in the SDT process; otherwise the SDT will not be able to
locate the correct code to be translated. Moreover, we want this Since RPC invocations are much more expensive than
synchronization to be as transparent to the SDT as possible, normal function calls, we want to minimize the frequency
to minimize code changes. of RPC invocation. To do so, we take a passive approach.
When creating shared memory, there are two possible That is, we do not convert an entry from the SDT to RPC
strategies: on-demand and reservation-based. On-demand map- unless it modifies the code cache. Again, we try to achieve
ping creates the shared memory at the very moment a new this goal without involving heavy program analysis. Instead,
memory region is required, e.g., when the SDT wants to add we leverage the regression tests that are usually distributed
a new memory region to the code cache. However, as the along with the source code. More specifically, we begin with
process address space is shared by all modules of a program, no entries being converted to RPC and gradually convert them
the expected address may not always be available in both until all regression tests pass.
the untrusted process and the SDT process. For this reason, While our approach can be improved with more automation
we choose the reservation-based strategy. That is, when the and program analysis, we leave these as future work because
process is initialized, we reserve (map) a large chunk of our main goal here is to design and validate that our solution
shared memory in both the untrusted process(es) and the SDT is effective against the new code cache injection attacks.
process. Later, any request for shared memory will be allocated
from this shared memory pool. Note that in modern operating
systems, physical memory resources are not mapped until the D. Permission Enforcement
reserved memory is accessed, so our reservation-based strategy
does not impose significant memory overhead. To enforce mandatory W⊕X, we leverage the delegation-
based sandbox architecture [21]. Specifically, we intercept
Once the shared memory pool is created, synchronization all system calls related to virtual memory management, and
can be done via inter-process communication (IPC). Specif- enforce the following policies in the SDT process:
ically, when the SDT allocates a new memory region for
the code cache, it informs the untrusted process(es) about (I) Memory can not be mapped as both writable and exe-
the base address and the size of this new memory region. cutable.
Having received this event, the untrusted process(es) maps a (II) When mapping a memory region as executable, the base
memory region with the same size at the same base address address and the size must come from the SDT process,
with the expected permission (RX). Similarly, whenever the and the memory is always mapped as RX.
untrusted process allocates memory that needs to be shared, a (III) The permission of non-writable memory cannot be
synchronization event is sent to the SDT process. changed.
C. Remote Procedure Call
E. Security Analysis
Writing RPC stubs for the SDT faces two problems:
argument passing and performance. Argument passing can In this section, we analyze the security of SDCG under
be problematic because of pointers. If a pointer points to a our threat model. First, we show that our design can enforce
memory location that is different between the untrusted process permanent W⊕X policy. The first system call policy ensures
and the SDT process, then the SDT ends up using incorrect that attackers cannot map memory that is both writable and
data and causes run-time errors. Vice versa, if the returned executable. The second policy ensures that attackers cannot
value from the SDT process contains pointers that point to switch memory from non-executable to executable. The combi-
data not copied back, the untrusted code ends up running nation of these two policies guarantees that no memory content
incorrectly. One possible solution for the stub to serialize can be mapped as both writable and executable, either at the
the object before passing it to the remote process instead of same time or alternately. Next, the last policy ensures that if
simply passing the pointer. Unfortunately, not all arguments there is critical data that the SDT depends on, it cannot be
have built-in serialization functionality. In addition, when modified by attackers. Finally, since the SDT is trusted and
an argument is a large object, performing serialization and its data is protected, the second policy can further ensure that
copy for every RPC invocation introduces high performance only SDT-verified content (e.g., code generated by the SDT)
overhead. Thus, in general, stub generation is not easy without can be executable. As a result, SDCG can prevent any code
support from the SDT or from program analysis. injection attack.
8
V. I MPLEMENTATION After this, any mmap request from the SDT allocates memory
from this pool (by changing the access permission) instead
We implemented two prototypes of SDCG, one for the of using the mmap system call. This guarantees any SDT
Google V8 JS engine [24], and the other for the Strata allocated region can be mapped at exactly the same address in
DBT [48]. Both prototypes were implemented on Linux. We both the SDT process and the untrusted process(es).
chose these two SDTs for the following reasons. First, JS
engines are one of the most widely deployed SDTs. At the After the sandbox is enabled, whenever the SDT calls
same time, they are also one of the most popular stepping mmap, SDCG generates a synchronized request to the un-
stones for launching attacks. Among all JS engines, we chose trusted process(es), and waits until the synchronization is done
V8 because it is open source, highly ranked, and there is before returning to the SDT. In the untrusted process, the
a disclosed exploit [43]. Second, DBTs have been widely synchronization event is handled by the trusted thread. It reads
used by security researchers to build various security solu- a synchronization request from the IPC channel and then
tions [8, 12, 25, 26, 36]. Among all DBTs, we chose Strata changes the access permission of the given region to the given
because 1) it has been used to implement many promising se- value. Since the parameters (base address, size and permission)
curity mechanisms, such as instruction set randomization [26], are passed through the read-only IPC channel and the trusted
instruction layout randomization [25], etc.; and 2) its academic thread does not use a stack, it satisfies our security policy for
background allowed us to have access to its source code, which mapping executable memory.
is required for implementation of SDCG.
Memory mapping in the untrusted process(es) is forwarded
to the SDT process by the system call interception mechanism
A. Shared Infrastructure of the sandbox. The request first goes through system call
filtering to ensure the security policy is enforced. SDCG then
The memory synchronization and system call filtering
checks where the request originated. If the request is from
mechanisms are specific to the target platform, but they can
the SDT, or is a special resource the SDT depends on (e.g.,
be shared among all SDTs.
mapping new modules needs to be synchronized for Strata),
1) Seccomp-Sandbox: Our delegation-based sandbox is the request is fulfilled from the shared memory pool. If it is
built upon the seccomp-sandbox [22] from Google Chrome. a legitimate request from the untrusted code, the request is
Although Google Chrome has switched to a less complicated fulfilled normally.
process sandbox based on seccomp-bpf [1], we found that
3) System Call Filtering: SDCG rejects the following types
the architecture of seccomp-sandbox serves our goal better.
of system calls.
Specifically, since seccomp only allows four system calls once
enabled, and not all system calls can be fulfilled by the broker • mmap with writable (PROT_WRITE) and executable
(e.g., mmap), the seccomp-sandbox introduced a trusted thread (PROT_EXEC) permission.
to perform system calls that cannot be delegated to the broker. • mprotect or mremap when the target region falls into
To prevent attacks on the trusted thread, the trusted thread a protected memory region.
operates entirely on CPU registers and does not trust any • mprotect with executable (PROT_EXEC) permission.
memory that is writable to the untrusted code. When the trusted
thread makes a system call, the system call parameters are SDCG maintains a list of protected memory regions. After
first verified by the broker, and then passed through a shared the SDT process is forked, it enumerates the memory mapping
memory that is mapped as read-only in the untrusted process. list through /proc/self/maps, and any region that is
As a result, even if the other threads in the same process are executable is included in the list. During runtime, when a new
compromised, they cannot affect the execution of the trusted executable region is created, it is added to the list; when a
thread. This provides a perfect foundation to securely build our region is unmapped, it is removed from the list. If necessary,
memory synchronization mechanism and system call filtering the SDT’s dynamic data can also be added to this list.
mechanism.
For Strata, this filtering is implemented by intercepting the
To enforce the mandatory W⊕X policy, we modified the related system calls (mmap, mremap, and mprotect). For
sandbox so that before entering sandbox mode, SDCG enu- V8 (integrated with the Google Chrome browser), we rely on
merates all memory regions and converts any WRX region to the seccomp-bpf filtering policies.
RX.
B. SDT Specific Handling
For RPC invocation, we also reused seccomp-sandbox’s
domain socket based communication channel. However, we did Next, we describe some implementation details that are
not leverage the seccomp mode in our current implementation specific to the target SDT.
for several reasons. First, it is not compatible with the new
seccomp-bpf-based sandbox used in Google Chrome. Second, 1) Implementation for Strata: Besides the code cache,
it intercepts too many system calls that are not required by many Strata-based security mechanisms also involve some
SDCG. More importantly, both Strata and seccomp-bpf provide critical metadata (e.g., the key to decrypt a randomized in-
enough capability for system call filtering. struction set) that needs to be protected. Otherwise, attackers
can compromise such data to disable or mislead critical func-
2) Shared Memory Pool: During initialization, SDCG re- tionalities of the security mechanisms. Thus, we extended the
serves a large amount of consecutive memory as a pool. This protection to Strata’s code, data, and the binary to be translated.
pool is mapped as shared (MAP_SHARED), not file backed Fortunately, since Strata directly allocates memory from mmap
(MAP_ANONYMOUS) and with no permission (PROT_NONE). and manages its own heap, this additional protection can be
9
easily supported by SDCG. Specifically, SDCG ensures that all from the program’s stack. This is not true for V8. In fact, many
the memory regions allocated by Strata are mapped as either objects used by V8 are allocated on the stack. Thus, during
read-only or inaccessible. Note that we do not need to protect RPC handling, the STD process may dereference pointers
Strata’s static data, because once the SDT process is forked, the pointing to the stack. Moreover, since the stack is assigned
static data is copy-on-write protected, i.e., while the untrusted during thread creation, it is difficult to ensure that the program
code could modify Strata’s static data, the modification cannot always allocates stack space from our shared memory pool.
affect the copy in the SDT process. As a result, we copy content between the two processes.
Fortunately, only 3 RPCs require a stack copy. Note that
Writing RPC stubs for Strata also reflects the differences in
because the content is copied to/from the same address, when
the attack model: since all dynamic data are mapped as read-
creating the trusted SDT process, we must assign it a new
only, any functionality that modified the data also needs to be
stack instead of relying on copy-on-write.
handled in the SDT process.
Another special case for Strata is the handling of process Writing RPC stubs for V8 is more flexible than Strata be-
creation, i.e., the clone system call. The seccomp-sandbox cause dynamic data is not protected. For this reason, we would
only handles the case for thread creation, which is sufficient prefer to convert functions that are invoked less frequently. To
for Google Chrome (and V8). But for Strata, we also need to achieve this goal, we followed two general principles. First,
handle process creation. The challenge for process creation is between the entry of the JS engine and the point where the
that once a memory region is mapped as shared, the newly code cache is modified, many functions could be invoked. If
created child process will also inherit this memory regions as we convert a function too high in the calling chain, and the
shared. Thus, once the untrusted code forks a new process, function does not result in modification of the code cache
this process also shares the same memory pool with its parent under another context, we end up introducing unnecessary RPC
and the SDT process. If we want to enforce a 1 : 1 serving overhead. For instance, the first time a regular expression is
model, we need to un-share the memory. Unfortunately, un- evaluated, it is compiled; but thereafter, the compiled code can
sharing memory under Linux is not easy: one needs to 1) map be retrieved from the cache. Thus, we want to convert functions
a temporary memory region, 2) copy the shared content to this that are post-dominated by operations that modify the code
temporary region, 3) unmap the original shared memory, 4) cache. Conversely, if we convert a function that is too low in
map a new shared memory region at exactly the same address, the calling chain, even though the invocation of this function
5) copy the content back, and 6) unmap the temporary memory always results in modification of the code cache, the function
region. At the same time, the child process is likely to either may be called from a loop, e.g., marking processes during
share the same binary as its parent, which means it can be garbage collection. This also introduces unnecessary overhead.
served by the same SDT; or call execve immediately after Thus, we also want to convert functions that dominate as many
the fork, which completely destroys the virtual address space modifications as possible. In our prototype implementation,
it inherited from its parent. For these reasons, we implemented since we did not use program analysis, these principles were
a N : 1 serving model for Strata, i.e., one SDT process applied empirically. In the end, we added a total of 20 RPC
serves multiple untrusted processes. The clone system call stubs.
can then be handled in the same way for both thread creation
and process creation. The only difference is that when a new VI. E VALUATION
memory region is allocated from the shared memory pool, all
processes need to be synchronized. In this section, we describe the evaluation of the ef-
fectiveness and performance overhead of our two prototype
2) Implementation for V8: Compared with Strata, the implementations.
biggest challenge for porting V8 to SDCG is the dynamic data
used by V8. Specifically, V8 has two types of dynamic data:
JS related data and its own internal data. The first type of A. Setup
data is allocated from custom heaps that are managed by V8 For our port of the Strata DBT, we measured the perfor-
itself. Similar to Strata’s heap, these heaps directly allocate mance overhead using SPEC CINT 2006 [56]. Our port of the
memory from mmap, thus SDCG can easily handle this type of V8 JS engine was based on revision 16619. The benchmark
data. The difficulty is from the second type of data, which we used to measure the performance overhead is the V8
is allocated from the standard C library (glibc on Linux). Benchmark distributed with the source code (version 7) [44].
This makes it challenging to track which memory region is All experiments were run on a workstation with one Intel Core
used by the JS engine. Clearly, we cannot make the standard i7-3930K CPU (6-core, 12-thread) and 32GB memory. The
C library allocate all the memory from the shared memory operating system is the 64-bit Ubuntu 13.04 with kernel 3.8.0-
pool. However, as mentioned earlier in the design section, 35-generic.
we have to share data via RPC and avoid serializing objects,
especially C++ objects, which can be complicated. To solve
this problem, we implemented a simple arena-based heap that B. Effectiveness
is backed by the shared memory pool and modified V8 to
In Section IV-E, we provided a security analysis of our
allocate certain objects from this heap. Only objects that are
system design, which showed that if implemented correctly,
involved in RPC need to be allocated from this heap, the rest
SDCG can prevent all code cache injection attacks. In this sec-
can still be allocated from the standard C library.
tion, we evaluate our SDCG-ported V8 prototype to determine
Another problem is the stack. Strata does not share the whether it can truly prevent the attack we demonstrated in
same stack as the translated program, so it never reads data Section III-C3.
10
The experiment was done using the same proof-of-concept iii) Two main threads that frequently access shared memory
code as described in Section III-C3. As the attack relies on a on a single CPU thread, trusted thread freely scheduled
race condition, we executed it 100 times. For the version that (affinity mask = {0},{*});
is protected by naive W⊕X enforcement, the attack was able iv) Two main threads on a single core, trusted thread freely
to inject shellcode into the code cache 91 times. For SDCG- scheduled (affinity mask = {0,1},{*});
ported version, all 100 attempts failed. v) All three threads on different cores (affinity mask =
{0},{2},{4}); and
C. Micro Benchmark vi) All three threads freely scheduled (affinity mask =
{*},{*},{*}).
The overhead introduced by SDCG comes from two major
sources: RPC invocation and cache coherency. Table II shows the result, using the 64-bit release build.
All the numbers are for RPC invocation, with return latency
1) RPC Overhead: To measure the overhead for each RPC omitted. Based on the result, it is clear that scheduling has a
invocation, we inserted a new field in the request header great impact on the RPC latency. If the two main threads are
to indicate when this request was sent. Upon receiving the not scheduled on the same CPU thread, the average latency
request, the handler calculates the time elapsed between this can exacerbate to 3x-4x slower. On the other hand, scheduling
and the current time. Similarly, we also calculated the time for the trusted thread has little impact on the RPC latency.
elapsed between the sending and receiving of return values. To This is expected because the trusted thread is only utilized for
eliminate the impact from cache synchronization, we pinned memory synchronization.
all threads (in both the untrusted process and the SDT process)
to a single CPU core. D. Macro Benchmark
The frequency of RPC invocation also effects overall over- In this section, we report the overall overhead SDCG
head, so we also collected this number during the evaluation. introduces. Since OS scheduling can have a large impact on
Table I shows the result from the V8 benchmark, using performance, for each benchmark suite, we evaluated two CPU
the 64-bit release build. The average latency for call request schedules. The first (Pinned) pins both the main threads from
is around 3-4 µs and the average latency for RPC return the untrusted process and the SDT process to a single core;
is around 4-5 µs. Thus, the average latency for an RPC and the second (Free) allows the OS to freely schedule all
invocation through SDCG’s communication channel is around threads.
8-9 µs. The number of RPC invocations is between 1,525 and 1) SPEC CINT 2006: Both the vanilla Strata and the
6,000. Since the input is fixed, this number is stable, with SDCG-ported Strata are built as 32-bit. The SPEC CINT
small fluctuations caused by garbage collection. Compared to 2006 benchmark suite is also compiled as 32-bit. Since all
the overall overhead presented in the next section, it follows benchmarks from the suite are single-threaded, the results of
that the larger the number of RPC invocations, the grater the different scheduling strategies only reflect the overhead caused
value of overhead. Among all RPC invocations, less than 24% by SDCG.
require a stack copy.
Table III shows the evaluation result. The first column
2) Cache Coherency Overhead: SDCG involves at least is the result of running natively. The second column is the
three concurrently running threads: the main thread in the result for Strata without SDCG. We use this as the baseline
untrusted process, the trusted thread in the untrusted process, for calculating the slowdown introduced by SDCG. The third
and the main thread in the SDT process. This number can column is the result for SDCG with pinned schedule, and the
increase if the SDT to be protected already uses multiple last column is the result for SDCG with free schedule. Since
threads. On a platform with multiple cores, these threads can the standard deviation is small (less than 1%), we omitted this
be scheduled to different cores. Since SDCG depends heavily information.
on shared memory, OS scheduling for these threads can also The corresponding slowdown is shown in Figure 4. For all
affect performance, i.e., cache synchronization between threads benchmarks, the slowdown introduced by SDCG is less than
executing on different cores introduces additional overhead. 6%. The overall (geometric mean) slowdown is 1.46% for the
In this section, we report this overhead at the RPC in- pinned schedule, and 2.05% for the free schedule.
vocation level. In the next section, we present its impact on Since SPEC CINT is a computation-oriented benchmark
overall performance. The evaluation also uses V8 benchmark. suite and Strata does a good job reducing the number of trans-
To reduce the possible combination of scheduling, we disabled lator invocations, we did not observe a significant difference
all other threads in V8, leaving only the aforementioned three between the pinned schedule and the free schedule.
threads. The Intel Core i7-3930K CPU on our testbed has
six cores. Each core has a dedicated 32KB L1 data cache 2) JavaScript Benchmarks: Our port of V8 JS engine was
and 256KB integrated L2 cache. A 12MB L3 cache is shared based on revision 16619. For better comparison with an SFI-
among all cores. When Hyperthreading is enabled, each core based solution [5], we performed the evaluation on both IA32
can execute two concurrent threads. and x64 release builds. The arena-based heap we implemented
was only enabled for SDCG-ported V8. To reduce the possible
Given the above configuration, we have tested the following combination of scheduling, we also disabled all other threads
scheduling: in V8.
i) All threads on a single CPU thread (affinity mask = {0}); Table IV shows the results for the IA32 build, and Table V
ii) All threads on a single core (affinity mask = {0,1}); shows the results for the x64 build. The first column is the
11
TABLE I: RPC Overhead During the Execution of V8 Benchmark.
Avg Call Latency Avg Return Latency # of Invocations Stack Copy (%) No Stack Copy (%)
Richards 4.70 µs 4.54 µs 1525 362 (23.74%) 1163 (76.26%)
DeltaBlue 4.28 µs 4.46 µs 2812 496 (17.64%) 2316 (82.36%)
Crypto 3.99 µs 4.28 µs 4596 609 (13.25%) 3987 (86.75%)
RayTrace 3.98 µs 4.00 µs 3534 715 (20.23%) 2819 (79.77%)
EarlyBoyer 3.87 µs 4.28 µs 5268 489 ( 9.28%) 4779 (90.72%)
RegExp 3.82 µs 5.06 µs 6000 193 ( 3.22%) 5807 (96.78%)
Splay 4.63 µs 5.04 µs 5337 1187 (22.24%) 5150 (77.76%)
NavierStokes 4.67 µs 4.82 µs 1635 251 (15.35%) 1384 (84.65%)
TABLE II: Cache Coherency Overhead Under Different Scheduling Strategies.
Schedule 1 Schedule 2 Schedule 3 Schedule 4 Schedule 5 Schedule 6
Richards 4.70 µs 13.76 µs 4.47 µs 14.25 µs 12.85 µs 13.37 µs
DeltaBlue 4.28 µs 13.29 µs 4.31 µs 13.85 µs 14.09 µs 15.84 µs
Crypto 3.99 µs 10.91 µs 3.98 µs 14.07 µs 12.47 µs 13.48 µs
RayTrace 3.98 µs 14.99 µs 4.05 µs 14.76 µs 13.15 µs 12.35 µs
EarlyBoyer 3.87 µs 13.70 µs 3.87 µs 14.27 µs 13.42 µs 13.47 µs
RegExp 3.82 µs 14.64 µs 3.85 µs 14.48 µs 13.55 µs 12.32 µs
Splay 4.63 µs 12.92 µs 4.49 µs 13.22 µs 13.36 µs 15.11 µs
NavierStokes 4.67 µs 12.06 µs 4.47 µs 13.02 µs 14.80 µs 12.65 µs
50.00%
SDCG
(Pinned)
50.00%
SDCG
(Pinned)
SDCG
(Free)
SDCG
(Free)
40.00%
40.00%
30.00%
30.00%
20.00%
20.00%
10.00%
10.00%
0.00%
0.00%
Ri
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Fig. 5: V8 Benchmark Slowdown (IA32). Fig. 6: V8 Benchmark Slowdown (x64).
Baseline SDCG (Pinned) SDCG (Free) Baseline SDCG (Pinned) SDCG (Free)
Richards 24913 (2.76%) 23990 (0.28%) 24803 (1.72%) Richards 25178 (3.39%) 24587 (2.31%) 25500 (3.24%)
DeltaBlue 25657 (3.31%) 24373 (0.43%) 25543 (3.86%) DeltaBlue 24324 (3.65%) 23542 (0.38%) 24385 (2.54%)
Crypto 20546 (1.61%) 19509 (1.27%) 19021 (1.95%) Crypto 21313 (3.16%) 20551 (0.26%) 20483 (2.57%)
RayTrace 45399 (0.38%) 42162 (0.75%) 43995 (6.46%) RayTrace 35298 (5.97%) 32972 (1.03%) 35878 (1.66%)
EarlyBoyer 37711 (0.61%) 34805 (0.27%) 34284 (0.82%) EarlyBoyer 32264 (4.42%) 30382 (0.61%) 30135 (1.04%)
RegExp 4802 (0.34%) 4251 (1.04%) 2451 (3.82%) RegExp 4853 (3.59%) 4366 (0.82%) 2456 (7.72%)
Splay 15391 (4.47%) 13643 (0.71%) 9259 (8.18%) Splay 13957 (6.02%) 12601 (2.92%) 7332 (9.85%)
NavierStokes 23377 (4.15%) 22586 (0.42%) 23518 (1.26%) NavierStokes 22646 (2.48%) 21844 (0.30%) 21468 (3.45%)
Score 21071 (0.72%) 19616 (0.35%) 17715 (1.86%) Score 19712 (3.57%) 18599 (0.62%) 16435 (1.03%)
TABLE IV: V8 Benchmark Results (IA32). The score is TABLE V: V8 Benchmark Slowdown (x64). The score is
the geometric mean over 10 executions of the benchmark the geometric mean over 10 executions of the benchmark
suite. Number in the parentheses is the standard deviation. suite. Number in the parentheses is the standard deviation.
baseline result; the second column is the result of SDCG- and the x64 build. For four benchmarks (Richards, DeltaBlue,
ported V8 with a pinned schedule; and the last column is the Crypto, and NavierStokes), the slowdown introduced by SDCG
result of SDCG-ported V8 with a free schedule. All results is less than 5%, which is negligible because they are similar to
are the geometric mean over 10 executions of the benchmark. the standard deviation. The other four benchmarks (RayTrace,
The number in the parentheses is the standard deviation as EarlyBoyer, RegExp, and Splay) have higher overhead, but
a percentage. As we can see, the fluctuation is small, with with a pinned schedule, the slowdown is within 11%, which
the baseline and a free schedule slightly higher than a pinned is much smaller than previous SFI-based solutions [5] (79%
schedule. on IA32).
The corresponding slowdown is shown in Figure 5 (for There are two major overhead sources. For RPC overhead,
IA32 build) and Figure 6 (for x64 build). Overall, we did we can see a clear trend that more RPC invocations (Table I),
not observe a significant difference between the IA32 build increase slowdown. However, the impact of cache coherency
12
6.00%
the thread to be swapped out of the CPU, which will extend
SDCG
(Pinned)
5.00%
SDCG
(Free)
the attack window.
4.00%
3.00%
2.00%
B. RPC Stub Generation
1.00%
To port a dynamic translator to SDCG, our current solution
0.00%
is to manually rewrite the source code. Even though the
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a good understanding of the internals of the translator. This
Fig. 4: SPEC CINT 2006 Slowdown. The baseline is the vanilla process can be improved or even automated through program
Strata. analysis. Firstly, our current RPC stub creation process is not
sound. That is, we relied on the test input. Thus, if a function
Native Strata SDCG (Pinned) SDCG (Free) is not invoked during testing, or the given parameter does not
trigger the function to modify the code cache, then we miss
perlbench 364 559 574 558
bzip2 580 600 613 602
this function. Second, to reduce performance overhead and
gcc 310 403 420 410 the attack surface, we want to create stubs only for functions
mcf 438 450 479 471 that 1) are post-dominated by operations that modify the code
gobmk 483 610 623 611 cache; and 2) dominate as many modification operations as
hmmer 797 777 790 777 possible. Currently, this is done empirically. Through program
sjeng 576 768 784 767
libquantum 460 463 511 474 analysis, we could systematically and more precisely identify
h264ref 691 945 980 971 these “key” functions. Finally, for the ease of development, our
omnetpp 343 410 450 428 prototype implementation uses shared memory to avoid deep
astar 514 546 587 563 copy of objects when performing RPC. While this strategy
xalancbmk 262 499 515 504
is convenient, it may introduce additional cache coherency
GEOMEAN 461 566 592 576 overhead. With the help of program analysis, we could replace
this strategy with object serialization, but only for data that is
TABLE III: SPEC CINT 2006 Results. Since the standard accessed during RPC.
deviation is small (less than 1%), we omitted this information.
C. Performance Tuning
overhead caused by different scheduling strategies is not
consistent. For some benchmarks (Richards, DeltaBlu, and In our current prototype implementations, the SDTs were
RayTrace), free scheduling is faster than pinned scheduling. not aware of our modification to their architectures. Since
For some benchmarks (Crypto and EarlyBoyer), overhead is their optimization strategy may not be ideal for SDCG, it is
almost the same, but for two benchmarks (RegExp and Splay), possible to further reduce the overhead by making the SDT be
the overhead under free scheduling is much higher than pinned aware of our modification. First, one major source of SDCG’s
scheduling. We believe this is because these two benchmarks runtime overhead is RPC invocation, and the overhead can be
depend more heavily on data (memory) access. Note that, reduced if we reduce the frequency of code cache modification.
unlike Strata, for SDCG-ported V8, we not only shared the This can be accomplished in several ways. For instance, we
code cache, but also shared the heaps used to store JS objects, can increase the threshold to trigger code optimization, use
for the ease of RPC implementation. Besides RPC frequency, more aggressive speculative translation, separate the garbage
this is another reason why we observed a higher overhead collection, etc.
compared with SDCG-ported Strata.
Second, in our implementations, we used the domain
socket-based IPC channel from the seccomp-sandbox. This
VII. D ISCUSSION
means for each RPC invocation, we need to enter the kernel
In this section, we discuss the limitations of this work and twice; and both the request/return data need to be copied
potential future work. to/from the kernel. While this approach is more secure (in the
sense that a sent request cannot be maliciously modified), if the
request is always untrusted, then using a faster communication
A. Reliability of Race Condition
channel (e.g., ring buffer) could further reduce the overhead.
Although we only showed the feasibility of the attack in
one scenario, the dynamic translator can be invoked under Third, we used the same service model as seccomp-
different situations, each of which has its own race condition sandbox in our prototypes. That is, RPC requests are served by
window. Some operations can be quick (e.g., patching), while a single thread in the SDT process. This strategy is sufficient
others may take longer. By carefully controlling how the for SDTs where different threads share the same code cache
translator is invoked, we can extend the race condition window (e.g., Strata) since modifications need to be serialized anyway
and make such attacks more reliable. to prevent a data race condition. However, this service model
can become a bottleneck when the SDT uses different code
In addition, OS scheduling can also affect the size of the caches for different thread (e.g., JS engines). For such SDTs,
attack window. For example, as we have discussed in the we need to create dedicated service threads in the SDT process
Section III, the invocation of mprotect is likely to cause to serve different threads in the untrusted process.
13
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