Graduate School and Research Center in Digital Sciences

Prevalence and impact of low-entropy packing schemes in the malware ecosystem

Mantovani, Alessandro; Aonzo, Simone; Ugarte-Pedrero, Xabier; Merlo, Alessio; Balzarotti, Davide

NDSS 2020, Network and Distributed System Security Symposium, 23-26 February 2020, San Diego, CA, USA

An open research problem on malware analysis is how to statically distinguish between packed and non-packed executables. This has an impact on antivirus software and malware analysis systems, which may need to apply different heuristics or to resort to more costly code emulation solutions to deal with the presence of potential packing routines. It can also affect the results of many research studies in which the authors adopt algorithms that are specifically designed for packed or non-packed binaries. Therefore, a wrong answer to the question “is this executable packed?” can make the difference between malware evasion and detection. It has long been known that packing and entropy are strongly correlated, often leading to the wrong assumption that a low entropy score implies that an executable is NOT packed. Exceptions to this rule exist, but they have always been considered as oneoff cases, with a negligible impact on any large scale experiment. However, if such an assumption might have been acceptable in the past, our experiments show that this is not the case anymore as an increasing and remarkable number of packed malware samples implement proper schemes to keep their entropy low. In this paper, we empirically investigate and measure this problem by analyzing a dataset of 50K low-entropy Windows malware samples. Our tests show that, despite all samples have a low entropy value, over 30% of them adopt some form of runtime packing. We then extended our analysis beyond the pure entropy, by considering all static features that have been proposed so far to identify packed code. Again, our tests show that even a state of the art machine learning classifier is unable to conclude whether a low-entropy sample is packed or not by relying only on features extracted with static analysis.

Document Bibtex

Title:Prevalence and impact of low-entropy packing schemes in the malware ecosystem
Type:Conference
Language:English
City:San Diego
Country:UNITED STATES
Date:
Department:Digital Security
Eurecom ref:6166
Copyright: © ISOC. Personal use of this material is permitted. The definitive version of this paper was published in NDSS 2020, Network and Distributed System Security Symposium, 23-26 February 2020, San Diego, CA, USA and is available at :
Bibtex: @inproceedings{EURECOM+6166, year = {2020}, title = {{P}revalence and impact of low-entropy packing schemes in the malware ecosystem}, author = {{M}antovani, {A}lessandro and {A}onzo, {S}imone and {U}garte-{P}edrero, {X}abier and {M}erlo, {A}lessio and {B}alzarotti, {D}avide}, booktitle = {{NDSS} 2020, {N}etwork and {D}istributed {S}ystem {S}ecurity {S}ymposium, 23-26 {F}ebruary 2020, {S}an {D}iego, {CA}, {USA}}, address = {{S}an {D}iego, {UNITED} {STATES}}, month = {02}, url = {http://www.eurecom.fr/publication/6166} }
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