Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E2E229B49230E335B1C24BE8DA642528765FE1DCD7C695B4E388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWegumTARhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsSERWYMd:Y7fUWeguXhhPhleMeDGCSPxeeWmHNW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c11734fc683c7b68 |
|
VISUAL
aHash
|
00262060f0f6f670 |
|
VISUAL
dHash
|
4cccdac3c1a4ac81 |
|
VISUAL
wHash
|
002620f0f8fefff0 |
|
VISUAL
colorHash
|
38200000e00 |
|
VISUAL
cropResistant
|
f0b898c3d0c0c170,c68d8d91cd64bece,08304c4c4c100000,4cccdac3c1a4ac81 |
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 70 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.
Pages with identical visual appearance (based on perceptual hash)