Takedown Analysis: $701M Seized – Hunting the Remaining Crypto Scam Infrastructure
Just saw the breaking news about the Dubai Police-led operation taking down nine scam centers and arresting 276 individuals. While seizing $701M is a massive win, it highlights the sheer scale of the "Pig Butchering" (Sha Zhu Pan) crypto-fraud infrastructure still active globally.
From a defensive perspective, these operations are notoriously hard to detect because they rely heavily on social engineering rather than automated exploits. However, once the victim is hooked, the technical footprint is often the same: custom web shells for backend management and unsigned "trading platform" clients delivered to the victims.
We've started hunting for the delivery phase of these scams by looking for suspicious unsigned binaries masquerading as legitimate crypto apps. If you're looking to bolster your detections, I recommend monitoring for process creation events involving binaries with crypto-related keywords that lack valid digital signatures.
Here is a KQL query for Microsoft Sentinel/SOAR to start hunting these unsigned binaries on your endpoints:
DeviceProcessEvents
| where Timestamp > ago(7d)
| where FolderPath endswith ".exe" or FolderPath endswith ".msi"
| where FileName has_any ("crypto", "trade", "invest", "finance", "wallet", "bourse")
| where IsSigned == false
| project Timestamp, DeviceName, AccountName, FileName, FolderPath, SHA256
| order by Timestamp desc
Additionally, many of these centers utilize commercial remote access tools (RATs) like AnyDesk or TeamViewer for "customer support." Correlating the installation of unsigned crypto apps with a spike in RDP/RAT traffic is a high-fidelity signal.
Is anyone else seeing specific TTPs associated with these scam centers in their environment? I'm particularly interested in how others are handling the DNS filtering side for these rotating domains.
Solid query. We actually took this a step further and added a correlation for network connections. These "trading" apps almost always connect to non-standard ports (>1024) on recently registered domains (creation ago(3d)
| where RemotePort > 1024
| where InitiatingProcessVersionInfo isnot null
| where InitiatingProcessVersionInfo.CompanyName == "Unknown"
| project Timestamp, DeviceName, RemoteUrl, RemotePort, InitiatingProcessFileName
It caught a finance employee trying to install a "Binance-Pro" updater last week that turned out to be a RedLine stealer variant.
The hardest part with these scams is the 'consent' aspect. The user wants to install the app, so endpoint AV often whitelists it if it isn't flagged as malware yet.
We've had success with AppLocker policies preventing unsigned binaries from running in the %AppData% or %UserProfile%\Downloads directories. It breaks a lot of the initial delivery vectors for these scam clients. It's noisy at first with user pushback, but it's saved us from a few potential losses.
Great post. From a DFIR perspective, when we do get images of these machines, we often find extensive leftovers from Web shells used to manage the 'wallet' backends. If you are doing forensic analysis, check your IIS/Apache logs for POST requests to obscure .php files receiving high entropy (Base64) strings. They often use the webshell_pass parameter.
Python snippet to check entropy in logs if you need it:
import math
def calculate_entropy(data):
if not data: return 0
entropy = 0
for x in range(256):
p_x = float(data.count(chr(x)))/len(data)
if p_x > 0:
entropy += - p_x*math.log(p_x, 2)
return entropy
# usage: print(calculate_entropy(log_line_payload))
Anything above 4.5 in a POST body usually warrants a closer look.
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