Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17623FF3050506A3B0183A2D4A636A35FB3D2D205CB235F0577F9D79E5FCBE64CD2A6A2 |
|
CONTENT
ssdeep
|
768:3eAs6s6s66Z/RHJ3EatT73As6s6/sxVb4ms9yd4ePA2:BXXX6Z/aXX8b4msHF2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c643993c679956e1 |
|
VISUAL
aHash
|
00002020e0deffff |
|
VISUAL
dHash
|
3534c4e7e6a43124 |
|
VISUAL
wHash
|
00003030f2feffff |
|
VISUAL
colorHash
|
07c00018000 |
|
VISUAL
cropResistant
|
56c6d215d5a6a4c6,c1e765a6a4310c24,319094464e4e36c6,3535e4c5e3e5a6a4,cf4bcbc658585859,47474d4d8b9b9b9b |
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 20 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.