Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F3733EA1E115AA7B006796C0B27AAF6B7BD3A304CA67460913FCC31D2FCBC44DD695E4 |
|
CONTENT
ssdeep
|
1536:B44xFYQFBf3nvE2Lk8xlIryk8eY4DnYSf:7WQFBf3nvE2LB/Aykpf1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ac2593caa4665bb5 |
|
VISUAL
aHash
|
3d3b031373b8fddf |
|
VISUAL
dHash
|
e9f31627e671c936 |
|
VISUAL
wHash
|
3d0303017138ffdf |
|
VISUAL
colorHash
|
07203010000 |
|
VISUAL
cropResistant
|
e9f31627e671c936,112931371d7c7e4f |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 80 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.