Pythons and Unicorns and Hancitor…Oh My! Decoding Binaries Through Emulation
Summary: Unit 42 describes using the Unicorn Engine in Python to run a Hancitor dropper's own x86 decoding routines inside an emulated environment, reusing the attacker's assembly rather than rewriting it, to extract embedded payloads from Microsoft Word documents. Running the resulting script against 10,000 unique Word documents first seen on August 15, 2016, the author decoded 9,967 stage 1 payloads and 8,851 stage 2 payloads, finding only 3 C2 URLs across the set and three XOR keys tied to different stage 2 droppers.
What's compelling: The payoff was just 3 C2 URLs across 8,851 decoded payloads, which shows how much bulk-analysis effort is needed to map even a single malware family's infrastructure - and the author notes the results were fairly unimpressive.
Read the original at Unit 42 Palo Alto Networks ↗
- Topics
- Malware
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