Memory Vulnerabilities Research Articles

CoMeT: Configurable Tagged Memory Extension.

Commodity processor architectures are releasing various instruction set extensions to support security solutions for the efficient mitigation of memory vulnerabilities. Among them, tagged memory extension (TME), such as ARM MTE and SPARC ADI, can prevent unauthorized memory access by utilizing tagged memory. However, our analysis found that TME has performance and security issues in practical use. To alleviate these, in this paper, we propose CoMeT, a new instruction set extension for tagged memory. The key idea behind CoMeT is not only to check whether the tag values in the address tag and memory tag are matched, but also to check the access permissions for each tag value. We implemented the prototype of CoMeT on the RISC-V platform. Our evaluation results confirm that CoMeT can be utilized to efficiently implement well-known security solutions, i.e., shadow stack and in-process isolation, without compromising security.

EM-Fuzz: Augmented Firmware Fuzzing via Memory Checking

Embedded systems are increasingly interconnected in the emerging application scenarios. Many of these applications are safety critical, making it a high priority to ensure that the systems are free from malicious attacks. This work aims to detect vulnerabilities, that could be exploited by adversaries to compromise functional correctness, in the embedded firmware, which is challenging especially due to the absence of source code. In particular, we propose EM-Fuzz, a firmware vulnerability detection technique that tightly integrates fuzzing with real-time memory checking. Based on the memory instrumentation, the firmware fuzzing can not only be guided by the traditional branch coverage to generate high-quality seeds to explore hard-to-reach regions but also by the recorded memory sensitive operations to continuously exercise sensitive regions which are prone to being attacked. More importantly, the instrumentation integrates real-time memory checkers to expose memory vulnerabilities, which is not well-supported by existing fuzzers without source code. The experiments on several real-world embedded firmware such as OpenSSL demonstrate that EM-Fuzz significantly improves the performance of state-of-the-art fuzzing tools, such as AFL and AFLFast, with the coverage improvements of 93.98% and 46.89%, respectively. Furthermore, EM-Fuzz exposes a total of 23 vulnerabilities, with an average of about 7-h per vulnerability. AFL and AFLFast together find 10 vulnerabilities, costing about 13 h and 10-h per vulnerability on average, respectively. Out of these 23 vulnerabilities, 16 are previously unknown and have been reported to the upstream product vendors, 7 of which have been assigned with unique CVE identifiers in the U.S. National Vulnerability Database.

Analyzing system software components using API model guided symbolic execution

Analyzing real-world software is challenging due to complexity of the software frameworks or APIs they depend on. In this paper, we present a tool, PROMPT, that facilitates the analysis of software components using API model guided symbolic execution. PROMPT has a specification component, PROSE, that lets users define an API model, which consists of a set of data constraints and life-cycle rules that define control-flow constraints among sequentially composed API functions. Given a PROSE model and a software component, PROMPT symbolically executes the component while enforcing the specified API model. PROMPT has been implemented on top of the KLEE symbolic execution engine and has been applied to Linux device drivers from the video, sound, and network subsystems and to some vulnerable components of BlueZ, the implementation of the Bluetooth protocol stack for the Linux kernel. PROMPT detected two new and four known memory vulnerabilities in some of the analyzed system software components.

Verification of dynamic memory allocators based on symbolic program execution

Subject of Research. The paper presents the study of vulnerability exploitation techniques in the implementation of dynamic memory allocation algorithms (glibc library allocator): Poisoned Null-byte, Overlapped Chunks, Fastbin Attack,Unsafe Unlink, House of Einherjar, House of Force, House of Spirit, House of Lore, Unsorted Bin Attack. Examples of vulnerability exploitation code and classification of the presented techniques are given in accordance with the Common Weakness Enumeration list. The modern methods and means of vulnerabilities detection are studied; their advantages and disadvantages are shown using the Heap Hopper framework as an example. Modern methods of appropriate software verification are considered. Method. The proposed software verification method combines the approaches of static analysis and symbolic execution using an accurate model of algorithms for dynamic memory allocation. In the compilation process of program being tested, the Kripke structure is created. Dynamic memory vulnerabilities are described by temporal logic formulas. The resulting structure and formulas are passed at the input of the model checking algorithm. Concrete-symbolic execution of the assembled binary file is performed. Vulnerability conditions expressed in the form of propositional logic formulas are checked for symbolic execution paths. Main Results. The practical use of the proposed approach to detection of dynamic memory vulnerabilities in software applications is shown. Symbolic execution is implemented in the form of a low-level debugger, which reduces the operating time of algorithms due to the execution of the application being tested on a real processor. Practical Relevance. The paper presents an integrated approach for solving the problem of automatic vulnerabilities detecting at different stages of the software development life cycle. This approach is applicable for verification of the similar implementations of dynamic memory allocators, such as ptmalloc, dlmalloc, tcmalloc, jemalloc and musl.

Memory Vulnerability Diagnosis for Binary Program

Vulnerability diagnosis is important for program security analysis. It is a further step to understand the vulnerability after it is detected, as well as a preparatory step for vulnerability repair or exploitation. This paper mainly analyses the inner theories of major memory vulnerabilities and the threats of them. And then suggests some methods to diagnose several types of memory vulnerabilities for the binary programs, which is a difficult task due to the lack of source code. The diagnosis methods target at buffer overflow, use after free (UAF) and format string vulnerabilities. We carried out some tests on the Linux platform to validate the effectiveness of the diagnosis methods. It is proved that the methods can judge the type of the vulnerability given a binary program.