C2 Activity: Sandboxes or Real Victims?
In my last diary[1], I mentioned that I was able to access screenshots exfiltrated by the malware sample. During the first analysis, there were approximately 460 JPEG files available. I continued to keep an eye on the host and the number slightly increased but not so much. My diary conclusion was that the malware looks popular seeing the number of screenshots but wait… Are we sure that all those screenshots are real victims? I executed the malware in my sandbox and probably other automated analysis tools were used to detonate the malware in a sandbox. This question popped up in my mind: How do have an idea about the ratio of automated tools VS. real victims?
I grabbed all the pictures in a local directory and wrote some lines of Python to analyze them. The main question is: how to detect if the screenshot has been taken in a sandbox or a real system? What we can check:
- The size of the screenshot (that matches the desktop)
- The percentage of unified color (usually, sandbox don’t have open windows and a limited set of icons on the desktop).
To « translate » this into Python, I used the classic library to work on image: pillow[2]. extcolors is a small library that works directly on colors[3].
#!/usr/bin/python3 import extcolors import PIL import os folder="screenshots" for image in os.listdir(folder): img = PIL.Image.open(folder+"/"+image) width, height = img.size colors, pixel_count = extcolors.extract_from_image(img) if width <= 1024 and height <= 768: print("Possible sandbox: %s : Size: %dx%d" % (image, width, height)) else: for c in colors: hexcolor = '%02x%02x%02x' % c[0] percentage = (c[1] / pixel_count) * 100 if percentage > 93 and hexcolor < "f00000": print("Possible sandbox: %s : Color: %s (%6.2f%%)" % (image,hexcolor, percentage))
After some tests, I decided to "flag" a screenshot as coming from a sandbox if the screen resolution is below 1024x768 and if we have >93% of a dark color (to match the classic blue, black or green backgrounds. Let's execute the scripts against the collected pictures:
Possible sandbox: 152114211370.jpg : Color: 000000 ( 94.25%) Possible sandbox: 152117757583.jpg : Color: 000000 ( 98.20%) Possible sandbox: 152127051988.jpg : Color: 000000 ( 95.09%) Possible sandbox: 152178310978.jpg : Size: 1024x768 Possible sandbox: 152129950226.jpg : Size: 800x600 Possible sandbox: 152115117436.jpg : Size: 800x600 Possible sandbox: 152135496106.jpg : Color: c7b199 ( 99.23%) Possible sandbox: 152119090512.jpg : Color: 000000 ( 99.37%) Possible sandbox: 152129464868.jpg : Color: 2974c7 ( 94.60%) Possible sandbox: 152153616774.jpg : Size: 800x600 Possible sandbox: 152137277200.jpg : Size: 800x600 Possible sandbox: 152157989841.jpg : Size: 1024x768 ...
Here are the results:
Some detected sandboxes:
[1] https://isc.sans.edu/forums/diary/Quick+Analysis+of+a+Modular+InfoStealer/27264/
[2] https://pillow.readthedocs.io/en/stable/
[3] https://pypi.org/project/extcolors/
Xavier Mertens (@xme)
Senior ISC Handler - Freelance Cyber Security Consultant
PGP Key
Comments
Anonymous
Dec 3rd 2022
9 months ago
Anonymous
Dec 3rd 2022
9 months ago
<a hreaf="https://technolytical.com/">the social network</a> is described as follows because they respect your privacy and keep your data secure. The social networks are not interested in collecting data about you. They don't care about what you're doing, or what you like. They don't want to know who you talk to, or where you go.
<a hreaf="https://technolytical.com/">the social network</a> is not interested in collecting data about you. They don't care about what you're doing, or what you like. They don't want to know who you talk to, or where you go. The social networks only collect the minimum amount of information required for the service that they provide. Your personal information is kept private, and is never shared with other companies without your permission
Anonymous
Dec 26th 2022
8 months ago
Anonymous
Dec 26th 2022
8 months ago
<a hreaf="https://defineprogramming.com/the-public-bathroom-near-me-find-nearest-public-toilet/"> nearest public toilet to me</a>
<a hreaf="https://defineprogramming.com/the-public-bathroom-near-me-find-nearest-public-toilet/"> public bathroom near me</a>
Anonymous
Dec 26th 2022
8 months ago
<a hreaf="https://defineprogramming.com/the-public-bathroom-near-me-find-nearest-public-toilet/"> nearest public toilet to me</a>
<a hreaf="https://defineprogramming.com/the-public-bathroom-near-me-find-nearest-public-toilet/"> public bathroom near me</a>
Anonymous
Dec 26th 2022
8 months ago
Anonymous
Dec 26th 2022
8 months ago
https://defineprogramming.com/
Dec 26th 2022
8 months ago
distribute malware. Even if the URL listed on the ad shows a legitimate website, subsequent ad traffic can easily lead to a fake page. Different types of malware are distributed in this manner. I've seen IcedID (Bokbot), Gozi/ISFB, and various information stealers distributed through fake software websites that were provided through Google ad traffic. I submitted malicious files from this example to VirusTotal and found a low rate of detection, with some files not showing as malware at all. Additionally, domains associated with this infection frequently change. That might make it hard to detect.
https://clickercounter.org/
https://defineprogramming.com/
Dec 26th 2022
8 months ago
rthrth
Jan 2nd 2023
8 months ago