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Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019, p.1849-1866
2019

Details

Autor(en) / Beteiligte
Titel
MalMax: Multi-Aspect Execution for Automated Dynamic Web Server Malware Analysis
Ist Teil von
  • Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019, p.1849-1866
Ort / Verlag
New York, NY, USA: ACM
Erscheinungsjahr
2019
Link zum Volltext
Quelle
ACM Digital Library
Beschreibungen/Notizen
  • This paper presents MalMax, a novel system to detect server-side malware that routinely employ sophisticated polymorphic evasive runtime code generation techniques. When MalMax encounters an execution point that presents multiple possible execution paths (e.g., via predicates and/or dynamic code), it explores these paths through counterfactual execution of code sandboxed within an isolated execution environment. Furthermore, a unique feature of MalMax is its cooperative isolated execution model in which unresolved artifacts (e.g., variables, functions, and classes) within one execution context can be concretized using values from other execution contexts. Such cooperation dramatically amplifies the reach of counterfactual execution. As an example, for Wordpress, cooperation results in 63% additional code coverage. The combination of counterfactual execution and cooperative isolated execution enables MalMax to accurately and effectively identify malicious behavior. Using a large (1 terabyte) real-world dataset of PHP web applications collected from a commercial web hosting company, we performed an extensive evaluation of MalMax. We evaluated the effectiveness of MalMax by comparing its ability to detect malware against VirusTotal, a malware detector that aggregates many diverse scanners. Our evaluation results show that MalMax is highly effective in exposing malicious behavior in complicated polymorphic malware. MalMax was also able to identify 1,485 malware samples that are not detected by any existing state-of-the-art tool, even after 7 months in the wild.
Sprache
Englisch
Identifikatoren
ISBN: 9781450367479, 145036747X
DOI: 10.1145/3319535.3363199
Titel-ID: cdi_acm_books_10_1145_3319535_3363199

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