By Lucas Davi, Ahmad-Reza Sadeghi
This e-book offers an in-depth examine return-oriented programming assaults. It explores numerous traditional return-oriented programming assaults and analyzes the effectiveness of security suggestions together with tackle house format randomization (ASLR) and the control-flow regulations carried out in defense watchdogs akin to Microsoft EMET.
Chapters additionally clarify the main of control-flow integrity (CFI), spotlight the advantages of CFI and speak about its present weaknesses. a number of enhanced and complex return-oriented programming assault ideas reminiscent of just-in-time return-oriented programming are presented.
Building safe Defenses opposed to Code-Reuse Attacks is a superb reference software for researchers, programmers and pros operating within the defense box. It presents advanced-level scholars learning computing device technological know-how with a complete evaluation and transparent knowing of significant runtime attacks.
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Extra resources for Building Secure Defenses Against Code-Reuse Attacks
CFI builds upon several assumptions to effectively defend against code-reuse attacks. Foremost, it assumes that code is not writable, and that an adversary cannot execute injected code from data memory. Both is ensured by enforcing the W ˚ X security model which is enabled by default on modern operating systems (cf. Sect. 4). However, this also means that original CFI is not applicable to selfmodifying code, or code that is generated just-in-time. As code is assumed to be immutable, Abadi et al.
For its policies in category ➀, ROPecker inspects each LBR entry to identify indirect branches that have redirected the control-flow to a gadget. This decision is based on the gadget database that ROPecker derived in the static analysis phase. ROPecker also inspects the program stack to predict future execution of gadgets. There is no direct policy check for indirect branches, but instead, possible gadgets are detected via a heuristic. 2 Practical CFI Implementations 37 its behavioral-based heuristic (category ➁) completely hinges on the assumption that instruction sequences will be short and that there will always be a chain of at least some threshold number of consecutive instruction sequences.
A gadget compiler that entirely focuses on constructing jump-oriented exploits is presented by Chen et al. . The compiler targets x86-compiled code and leverages the so-called combinational gadget terminating in a CALL-JMP sequence to invoke a system call in a jump-oriented attack. Whereas the previously discussed gadget compilers focused on a particular processor platform, Dullien et al.  introduce a gadget discovery tool that operates platform-independent by decompiling assembler instructions to an intermediate language called REIL.