Code injection

Abstract: Return-oriented programming is an effective code-reuse attack in which short code sequences ending in a ret instruction are found within existing binaries and executed in arbitrary order by taking control of the stack. This allows for Turing-complete behavior in the target program without the need for injecting attack code, thus significantly negating current code injection defense efforts (e.g., W⊕X). On the other hand, its inherent characteristics, such as the reliance on the stack and the consecutive execution of return-oriented gadgets, have prompted a variety of defenses to detect or prevent it from happening.In this paper, we introduce a new class of code-reuse attack, called jump-oriented programming. This new attack eliminates the reliance on the stack and ret instructions (including ret-like instructions such as pop+jmp) seen in return-oriented programming without sacrificing expressive power. This attack still builds and chains functional gadgets, each performing certain primitive operations, except these gadgets end in an indirect branch rather than ret. Without the convenience of using ret to unify them, the attack relies on a dispatcher gadget to dispatch and execute the functional gadgets. We have successfully identified the availability of these jump-oriented gadgets in the GNU libc library. Our experience with an example shellcode attack demonstrates the practicality and effectiveness of this technique.

Abstract: As AJAX applications gain popularity, client-side JavaScript code is becoming increasingly complex. However, few automated vulnerability analysis tools for JavaScript exist. In this paper, we describe the first system for exploring the execution space of JavaScript code using symbolic execution. To handle JavaScript code’s complex use of string operations, we design a new language of string constraints and implement a solver for it. We build an automatic end-to-end tool, Kudzu, and apply it to the problem of finding client-side code injection vulnerabilities. In experiments on 18 live web applications, Kudzu automatically discovers 2 previously unknown vulnerabilities and 9 more that were previously found only with a manually-constructed test suite.

Abstract: Binary code injection into an executing program is a common form of attack. Most current defenses against this form of attack use a 'guard all doors' strategy, trying to block the avenues by which execution can be diverted. We describe a complementary method of protection, which disrupts foreign code execution regardless of how the code is injected. A unique and private machine instruction set for each executing program would make it difficult for an outsider to design binary attack code against that program and impossible to use the same binary attack code against multiple machines. As a proof of concept, we describe a randomized instruction set emulator (RISE), based on the open-source Valgrind x86-to-x86 binary translator. The prototype disrupts binary code injection attacks against a program without requiring its recompilation, linking, or access to source code. The paper describes the RISE implementation and its limitations, gives evidence demonstrating that RISE defeats common attacks, considers how the dense x86 instruction set affects the method, and discusses potential extensions of the idea.

Abstract: It is critical to secure the Industrial Internet of Things (IIoT) devices because of potentially devastating consequences in case of an attack. Machine learning (ML) and big data analytics are the two powerful leverages for analyzing and securing the Internet of Things (IoT) technology. By extension, these techniques can help improve the security of the IIoT systems as well. In this paper, we first present common IIoT protocols and their associated vulnerabilities. Then, we run a cyber-vulnerability assessment and discuss the utilization of ML in countering these susceptibilities. Following that, a literature review of the available intrusion detection solutions using ML models is presented. Finally, we discuss our case study, which includes details of a real-world testbed that we have built to conduct cyber-attacks and to design an intrusion detection system (IDS). We deploy backdoor, command injection, and Structured Query Language (SQL) injection attacks against the system and demonstrate how a ML-based anomaly detection system can perform well in detecting these attacks. We have evaluated the performance through representative metrics to have a fair point of view on the effectiveness of the methods.