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Integer-Overflow-to-Buffer-Overflow (IO2BO) vulnerabilities can be exploited by attackers to cause severe damages to computer systems. In this paper, we present the design and implementation of IntTracker, an efficient dynamic tracking technique for detecting IO2BO vulnerabilities in C/C++ programs. IntTracker utilizes a static taint analysis to select potential overflow sites that are integer operations along critical paths, from sources that are program points reading values from users, to sinks that are memory allocation sites. It then instruments overflow checks at the selected sites. Instead of producing warnings once integer overflows occur, IntTracker replaces the overflown value with a very large and rarely used integer value (dirty value), and treats such the value as an overflow tag. Tag propagation is performed by the existing program operations without any instrumentation as operations on dirty values often produce dirty values. Propagation can be automatically cut off by sanitization routines as they could prevent dirty values from affecting further program execution. IntTracker monitors whether any dirty value is used at a sink to detect IO2BO vulnerabilities. We evaluate IntTracker on 3444 programs of the NIST's SAMATE reference dataset, the SPEC CIN-T2000 benchmarks and 34 IO2BO bugs in real world. The experimental results show that IntTracker is effective in detecting harmful IO2BO vulnerabilities while bypassing false positives introduced by sanitization routines. Meanwhile, the runtime overhead is negligible, averaging about 0.69%. In contrast, IntPatch, the state of the art, produces a lot more false positives and has a higher overhead.

Privacy protection is an essential part of information security. The use of shared resources demands more privacy and security protection, especially in cloud computing environments. Side-channel attacks based on CPU cache utilize shared CPU caches within the same physical device to compromise the system’s privacy (encryption keys, program status, etc.). Information is leaked through channels that are not intended to transmit information, jeopardizing system security. These attacks have the characteristics of both high concealment and high risk. Despite the improvement in architecture, which makes it more difficult to launch system intrusion and privacy leakage through traditional methods, side-channel attacks ignore those defenses because of the shared hardware. Difficult to be detected, they are much more dangerous in modern computer systems. Although some researchers focus on the survey of side-channel attacks, their study is limited to cryptographic modules such as Elliptic Curve Cryptosystems. All the discussions are based on real-world applications (e.g., Curve25519), and there is no systematic analysis for the related attack and security model. Firstly, this paper compares different types of cache-based side-channel attacks. Based on the comparison, a security model is proposed. The model describes the attacks from four key aspects, namely, vulnerability, cache type, pattern, and range. Through reviewing the corresponding defense methods, it reveals from which perspective defense strategies are effective for side-channel attacks. Finally, the challenges and research trends of CPU cache-based side-channel attacks in both attacking and defending are explored. The systematic analysis of CPU cache-based side-channel attacks highlights the fact that these attacks are more dangerous than expected. We believe our survey would draw developers’ attention to side-channel attacks and help to reduce the attack surface in the future.

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