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Malware analysis is an essential task to understand infection campaigns, the behavior of malicious codes, and possible ways to mitigate threats. Malware analysis also allows better assessment of attacker’s capabilities, techniques, and processes. Although a substantial amount of previous work provided a comprehensive analysis of the international malware ecosystem, research on regionalized, country, and population-specific malware campaigns have been scarce. Moving towards addressing this gap, we conducted a longitudinal (2012-2020) and comprehensive (encompassing an entire population of online banking users) study of MS Windows desktop malware that actually infected Brazilian bank’s users. We found that the Brazilian financial desktop malware has been evolving quickly: it started to make use of a variety of file formats instead of typical PE binaries, relied on native system resources, and abused obfuscation technique to bypass detection mechanisms. Our study on the threats targeting a significant population on the ecosystem of the largest and most populous country in Latin America can provide invaluable insights that may be applied to other countries’ user populations, especially those in the developing world that might face cultural peculiarities similar to Brazil’s. With this evaluation, we expect to motivate the security community/industry to seriously considering a deeper level of customization during the development of next generation anti-malware solutions, as well as to raise awareness towards regionalized and targeted Internet threats. 

A promising avenue for improving the effectiveness of behavioral-based malware detectors is to leverage two-phase detection mechanisms. Existing problem in two-phase detection is that after the first phase produces borderline decision, suspicious behaviors are not well contained before the second phase completes. This paper improves CHAMELEON, a framework to realize the uncertain environment. CHAMELEON offers two environments: standard–for software identified as benign by the first phase, and uncertain–for software received borderline classification from the first phase. The uncertain environment adds obstacles to software execution through random perturbations applied probabilistically. We introduce a dynamic perturbation threshold that can target malware disproportionately more than benign software. We analyzed the effects of the uncertain environment by manually studying 113 software and 100 malware, and found that 92% malware and 10% benign software disrupted during execution. The results were then corroborated by an extended dataset (5,679 Linux malware samples) on a newer system. Finally, a careful inspection of the benign software crashes revealed some software bugs, highlighting CHAMELEON's potential as a practical complementary antimalware solution.