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What is hyperhives-macos-infostealer-analysis?

darksp33d/hyperhives-macos-infostealer-analysis — explained in plain English

Analysis updated 2026-05-18

29PythonAudience · developerComplexity · 4/5LicenseSetup · hard

In one sentence

A researcher's full writeup and detection rules for a Mac targeting infostealer delivered through a fake job interview scam.

Mindmap

mindmap
  root((infostealer analysis))
    What it does
      Analyzes a real infostealer
      Recovers hidden config
      Attributes the campaign
    Tech stack
      Python
      Docker
      YARA and Sigma
    Use cases
      Load detection rules
      Study attack delivery
      Feed threat intel platforms
    Audience
      Security researchers
    Setup
      Isolated Docker lab
      Sample placement
      Run decrypt script

Code map

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What do people build with it?

USE CASE 1

Load the included YARA and Sigma rules into your own security monitoring tools.

USE CASE 2

Study how a real fake job interview malware campaign was built and delivered.

USE CASE 3

Import the STIX bundle or ATT&CK Navigator layer into a threat intelligence platform.

USE CASE 4

Reproduce the static analysis safely inside the provided isolated Docker lab.

What is it built with?

PythonDockerYARASigma

How does it compare?

darksp33d/hyperhives-macos-infostealer-analysisdabit3/agent-hooks-in-depthyousseeff20/fixpy
Stars292929
LanguagePythonPythonPython
Setup difficultyhardmoderateeasy
Complexity4/53/51/5
Audiencedeveloperdevelopervibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Reproducing the analysis needs Docker and the original malware sample, which is not included.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

So what is it?

This repository is a security researcher's writeup of a real malware campaign, not the malware itself. It documents a Rust based infostealer that targeted Apple computers, delivered through a fake job interview scam on the hiring platform Wellfound, formerly known as AngelList. An attacker using the name Felix and posing as a company called HyperHive contacted job applicants, built trust over several emails, then asked them to check a diagnostics log in a fake product, which actually ran a hidden command that downloaded and executed the malware. The repository walks through how the researcher took the captured program apart. Using an isolated, network disabled Docker lab and emulation tools, they recovered all 571 encrypted configuration values hidden inside the roughly 8.5 megabyte program, including the command and control server addresses it phones home to, a debugging service identifier that helped tie the malware to its operators, and a list of 276 Chrome browser extensions it specifically looks for, mostly cryptocurrency wallets and password managers. Based on the techniques used, the researcher attributes the campaign to a group associated with North Korea's so called Contagious Interview operation, which is known for using fake job offers to trick developers into running malware. The findings are organized as several standard threat intelligence file formats: a plain text list of indicators of compromise, detection rules in the YARA and Sigma formats that defenders can load into their own security tools, a structured STIX 2.1 bundle, and a layer file for the MITRE ATT&CK Navigator tool that maps the malware's behavior to known attack techniques. The project is written mostly in Python, covers the researcher's full analysis methodology from initial discovery through decryption, and is released under the MIT license so that other defenders can freely reuse the detection rules and indicators. The full README is longer than what was shown.

Copy-paste prompts

Prompt 1
Summarize how the Wellfound job interview lure led to malware execution in this report.
Prompt 2
Explain what the decrypt_all.py script does to recover the 571 configuration values.
Prompt 3
How do the YARA and Sigma rules in this repo detect the HyperHives infostealer?
Prompt 4
What does the ATT&CK Navigator layer in this repo cover?

Frequently asked questions

What is hyperhives-macos-infostealer-analysis?

A researcher's full writeup and detection rules for a Mac targeting infostealer delivered through a fake job interview scam.

What language is hyperhives-macos-infostealer-analysis written in?

Mainly Python. The stack also includes Python, Docker, YARA.

What license does hyperhives-macos-infostealer-analysis use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is hyperhives-macos-infostealer-analysis to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is hyperhives-macos-infostealer-analysis for?

Mainly developer.

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