When analyzing malware samples, a human analyst is typically interested in understanding/recovering a specific algorithms of the given sample. In the case of Conficker, for example, she might be interested in extracting the domain generation algorithm
such that she can understand what domains are currently and in the future used by the malware. Or for spam bots, she might be interested in how the malware downloads spam templates, decodes them, and then generates the actual spam messages. Or for bots, she might be interested in understanding how binary updates are downloaded, decoded, and then executed.
In each case, the binary itself encodes the algorithm, but it is cumbersome and hard work to understand all of this. Thus it would be useful to have a tool that enables a malware analyst to automatically
extract from a given binary sample the relevant algorithm related to a specific task. In a paper that will be presented at the 31st IEEE Symposium on Security & Privacy
we introduce Inspector Gadget
, a tool that implements exactly this. A gadget encapsulates all code related to a specific task and can be executed in a stand-alone fashion. A gadget player
can take a gadget and replay it, for example to determine which domains are currently used by Conficker, or download and decode an update for a bot binary. Furthermore, we introduce an approach to revert gadget based on a enhanced brute-force algorithm: this is useful to understand the effects of malware in detail and we can (in certain cases) also revert obfuscation algorithms, i.e., to understand what data has been exfiltrated by a given sample. The full paper
has all the details and describes Inspector Gadget in more depth. And if you are interested in the topic, you should also read the paper by Caballero et al. on BCR
(paper title is "Binary Code Extraction and Interface Identification for Security Applications").
Unfortunately, malicious software is still an unsolved problem and a major threat on the Internet. An important component in the fight against malicious software is the analysis of malware samples: Only if an analyst understands the behavior of a given sample, she can design appropriate countermeasures. Manual approaches are frequently used to analyze certain key algorithms, such as downloading of encoded updates, or generating new DNS domains for command and control purposes.
In this paper, we present a novel approach to automatically extract, from a given binary executable, the algorithm related to a certain activity of the sample. We isolate and extract these instructions and generate a so-called gadget, i.e., a stand-alone component that encapsulates a specific behavior. We make sure that a gadget can autonomously perform a specific task by including all relevant code and data into the gadget such that it can be executed in a self-contained fashion.
Gadgets are useful entities in analyzing malicious software: In particular, they are valuable for practitioners, as understanding a certain activity that is embedded in a binary sample (e.g., the update function) is still largely a manual and complex task. Our evaluation with several real-world samples demonstrates that our approach is versatile and useful in practice.
The full paper is available at http://www.iseclab.org/papers/ieee_sp10_inspector_gadget.pdf
and will be presented in May at the 31st IEEE Symposium on Security & Privacy
. The paper was joint work with Clemens Kolbitsch, Christopher Kruegel, and Engin Kirda - all members of the International Secure Systems Lab