1,385 research outputs found
Adaptive just-in-time code diversification
We present a method to regenerate diversified code dynamically in a Java bytecode JIT compiler, and to update the diversification frequently during the execution of the program. This way, we can significantly reduce the time frame in which attackers can let a program leak useful address space information and subsequently use the leaked information in memory exploits. A proof of concept implementation is evaluated, showing that even though code is recompiled frequently, we can achieved smaller overheads than the previous state of the art, which generated diversity only once during the whole execution of a program
Runtime protection via dataflow flattening
Software running on an open architecture, such as the PC, is vulnerable to inspection and modification. Since software may process valuable or sensitive information, many defenses against data analysis and modification have been proposed. This paper complements existing work and focuses on hiding data location throughout program execution. To achieve this, we combine three techniques: (i) periodic reordering of the heap, (ii) migrating local variables from the stack to the heap and (iii) pointer scrambling. By essentialy flattening the dataflow graph of the program, the techniques serve to complicate static dataflow analysis and dynamic data tracking. Our methodology can be viewed as a data-oriented analogue of control-flow flattening techniques. Dataflow flattening is useful in practical scenarios like DRM, information-flow protection, and exploit resistance. Our prototype implementation compiles C programs into a binary for which every access to the heap is redirected through a memory management unit. Stack-based variables may be migrated to the heap, while pointer accesses and arithmetic may be scrambled and redirected. We evaluate our approach experimentally on the SPEC CPU2006 benchmark suit
x86 instruction reordering for code compression
Runtime executable code compression is a method which uses standard data compression methods and binary machine code transformations to achieve smaller file size, yet maintaining the ability to execute the compressed file as a regular executable. With a disassembler, an almost perfect instructional and functional level disassembly can be generated. Using the structural information of the compiled machine code each function can be split into so called basic blocks. In this work we show that reordering instructions within basic blocks using data flow constraints can improve code compression without changing the behavior of the code. We use two kinds of data affection (read, write) and 20 data types including registers: 8 basic x86 registers, 11 eflags, and memory data. Due to the complexity of the reordering, some simplification is required. Our solution is to search local optimum of the compression on the function level and then combine the results to get a suboptimal global result. Using the reordering method better results can be achieved, namely the compression size gain for gzip can be as high as 1.24%, for lzma 0.68% on the tested executables
Improving the Performance and Endurance of Persistent Memory with Loose-Ordering Consistency
Persistent memory provides high-performance data persistence at main memory.
Memory writes need to be performed in strict order to satisfy storage
consistency requirements and enable correct recovery from system crashes.
Unfortunately, adhering to such a strict order significantly degrades system
performance and persistent memory endurance. This paper introduces a new
mechanism, Loose-Ordering Consistency (LOC), that satisfies the ordering
requirements at significantly lower performance and endurance loss. LOC
consists of two key techniques. First, Eager Commit eliminates the need to
perform a persistent commit record write within a transaction. We do so by
ensuring that we can determine the status of all committed transactions during
recovery by storing necessary metadata information statically with blocks of
data written to memory. Second, Speculative Persistence relaxes the write
ordering between transactions by allowing writes to be speculatively written to
persistent memory. A speculative write is made visible to software only after
its associated transaction commits. To enable this, our mechanism supports the
tracking of committed transaction ID and multi-versioning in the CPU cache. Our
evaluations show that LOC reduces the average performance overhead of memory
persistence from 66.9% to 34.9% and the memory write traffic overhead from
17.1% to 3.4% on a variety of workloads.Comment: This paper has been accepted by IEEE Transactions on Parallel and
Distributed System
Recommended from our members
Building Reliable Software for Persistent Memory
Persistent memory (PMEM) technologies preserve data across power cycles and provide performance comparable to DRAM. In emerging computer systems, PMEM will operate on the main memory bus, becoming byte-addressable and cache-coherent. One key feature enabled by persistent memory is to allow software directly accessing durable data using the CPU’s load/store instructions, even from the user-space.However, building reliable software for persistent memory faces new challenges from two aspects: crash consistency and fault tolerance. Maintaining crash consistency requires the ability to recover data integrity in the event of system crashes. Using load/store instructions to access durable data introduces a new programming paradigm, that is prone to new types of programming errors. Fault tolerance involves detecting and recovering from persistent memory errors, including memory media errors and scribbles from software bugs. With direct access, file systems and user-space applications have to explicitly manage these errors, instead of relying on convenient functions from lower I/O stacks.We identify unique challenges in improving reliability for PMEM-based software and propose solutions. The thesis first introduces NOVA-Fortis, a fault-tolerant PMEM file system incorporating replication, checksums, and parity for protecting the file system’s metadata and the user’s file data. NOVA-Fortis is both fast and resilient in the face of corruption due to media errors and software bugs.NOVA-Fortis only protects file data via the read() and write() system calls. When an application memory-maps a PMEM file, NOVA-Fortis has to disable file data protection because mmap() leaves the file system unaware of updates made to the file. For protecting memory-mapped PMEM data, we present Pangolin, a fault-tolerant persistent object library to protect an application’s objects from persistent memory errors.Writing programs to ensure crash consistency in PMEM remains challenging. Recovery bugs arise as a new type of programming error, preventing a post-crash PMEM file from recovering to a consistent state. Thus, we design two debugging tools for persistent memory programming: PmemConjurer and PmemSanitizer. PmemConjurer is a static analyzer using symbolic execution to find recovery bugs without running a compiled program. PmemSanitizer contains compiler instrumentation and run-time recovery bug analysis, compensating PmemConjurer with multi-threading support and store reordering tests
Improved Kernel Security Through Code Validation, Diversification, and Minimization
The vast majority of hosts on the Internet, including mobile clients, are running one of three commodity, general-purpose operating system families. In such operating systems the kernel software executes at the highest processor privilege level. If an adversary is able to hijack the kernel software then by extension he has full control of the system. This control includes the ability to disable protection mechanisms and hide evidence of compromise.
The lack of diversity in commodity, general-purpose operating systems enables attackers to craft a single kernel exploit that has the potential to infect millions of hosts. If enough variants of the vulnerable software exist, then mass exploitation is much more difficult to achieve. We introduce novel kernel diversification techniques to improve kernel security.
Many modern kernels are self-patching; they modify themselves at run-time. Self-patching kernels must therefore allow kernel code to be modified at run-time. To prevent code injection attacks, some operating systems and security mechanisms enforce a W^X memory protection policy for kernel code. This protection policy prevents self-patching kernels from applying patches at run-time. We introduce a novel run-time kernel instruction-level validation technique to validate the integrity of patches at run-time.
Kernels shipped with general-purpose operating systems often contain extraneous code. The code may contain exploitable vulnerabilities or may be pieced together using return/jump-oriented programming to attack the system. Code-injection prevention techniques do not prevent such attacks. We introduce a novel run-time kernel minimization technique to improve kernel security.
We show that it is possible to strengthen the defenses of commodity general-purpose computer operating systems by increasing the diversity of, validating the integrity of, and ensuring the minimality of the included kernel components without modifying the kernel source code. Such protections can therefore be added to existing widely-used unmodified operating systems to prevent malicious software from executing in supervisor mode
- …