Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11F53EAB6A25439B3416347D2B42A929A31D7415EEE13493093FC4FEDE7E3CE5982EC81 |
|
CONTENT
ssdeep
|
768:OB57eDx5VRYDVm6lvzmaxVcq9r0eeiJRZCSLL2PweHrvzmaxxXjp:wmaxD9r0eeiJRZJ2DXmaxB9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc916ac96ec33269 |
|
VISUAL
aHash
|
fd9f8f8f9bbfc181 |
|
VISUAL
dHash
|
6b3c383c3332032f |
|
VISUAL
wHash
|
f99f8787899b8181 |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
6b3c383c3332032f,82e0ea82b0b880f0,e6662815a48ea25c,b6b3993314aca964,21de21a6a63696a6 |
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 6995 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)