Since its public debut in October 2025, nightmare has shortly turn into an important software for malware analysts searching for to streamline static and dynamic evaluation workflows.
Developed by Elastic Safety Labs, nightmare brings collectively mature open-source reverse engineering elements beneath a unified Python API.
Relatively than forcing customers to juggle disparate dependencies, nightmare leverages Rizin through rz-pipe for disassembly and the Unicorn engine for light-weight emulation.
This cohesive design empowers researchers to quickly craft configuration extractors, carve IoCs, and automate recurring evaluation duties.
Rising from a necessity to cut back code duplication throughout Elastic’s inner tooling, nightmare builds on practices honed over hundreds of pattern analyses.
Elastic analysts famous that many proprietary scripts suffered from fragile dependency chains and inconsistent abstractions.
By encapsulating widespread patterns—similar to sample matching, instruction emulation, and cross-reference enumeration—inside a strong library, nightMARE supplies a secure basis for each seasoned and novice reverse engineers.
Upon set up, nightmare exposes three major modules: evaluation, core, and malware. The evaluation module integrates Rizin to allow disassembly, hex-pattern searches, and performance enumeration.
The core module presents utilities for bitwise operations, regex-based extraction, and information casting.
Lastly, the malware module teams family-specific extractors—starting from Smokeloader to LUMMA—into versioned sub-packages that exhibit real-world makes use of of the API.
Elastic researchers recognized a big spike in LUMMA stealer campaigns in mid-2025, underscoring the worth of speedy configuration extraction.
By means of nightmare’s emulation capabilities, analysts can instantiate a WindowsEmulator, register Import Tackle Desk (IAT) hooks on APIs similar to Sleep, and execute focused code sequences in seconds.
By intercepting decryption routines in-process, nightMARE automates the restoration of C2 domains with out guide unpacking or debugger-driven tracing.
An infection Mechanism and Emulation-Pushed Extraction
nightMARE’s emulation framework presents a light-weight various to full-scale sandboxing. Think about the widespread method the place malware invokes Sleep earlier than continuing to C2 decryption.
The next code snippet demonstrates how nightMARE’s WindowsEmulator hooks Sleep in a LUMMA pattern, capturing timing conduct and enabling uninterrupted emulation:-
import pathlib
from nightMARE.evaluation import emulation
def sleephook(emu: emulation.WindowsEmulator, args):
print(f”Sleep {emu.unicorn.reg_read(emulation.unicorn.x86_const.UC_X86_REG_ECX)} ms”)
emu.do_return()
def major():
path = pathlib.Path(r”C:samplesDismHost.exe”)
emu = emulation.WindowsEmulator(is_32bits=False)
emu.load_pe(path.read_bytes(), stack_size=0x10000)
emu.enable_iat_hooking()
emu.set_iat_hook(b”KERNEL32.dll!Sleep”, sleephook)
emu.unicorn.emu_start(0x140006404, 0x140006412)
LUMMA manually pushes Steam profile information for decryption (Supply – Elastic)
By intercepting the Sleep name, the emulator advances previous timing obfuscation and resumes execution on the subsequent instruction.
Mixed with emu.get_data() and emu.get_xrefs_from(), analysts reconstruct decryption key and nonce addresses, allocate reminiscence buffers, and invoke the malware’s ChaCha20 routine immediately.
In the end, nightMARE outputs a decrypted checklist of C2 domains, prepared for menace intelligence ingestion.
With model 0.16, Elastic Safety Labs continues to increase nightMARE’s repertoire, including emulation help for extra API hooks, enhancing pattern-matching accuracy, and refining malware module templates.
As rising threats exploit novel obfuscation and packing schemes, nightMARE stands poised to speed up evaluation pipelines and empower the group’s collective protection.
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