Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FA452AF0E22C21BC404F03E495252EAC735E31B6B592496899BCDB389AE3D54CE1F85F |
|
CONTENT
ssdeep
|
3072:WeZNeLTpSnScVi1DVCqyTYUegDxc9UqbhsyjhsybPaiyJoy5d:WxCS9yp2hsghsmc5d |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3c0aa2ff7d568c0 |
|
VISUAL
aHash
|
ff7f783c20183cff |
|
VISUAL
dHash
|
6bc190c8e96be369 |
|
VISUAL
wHash
|
ff7d7834001838bd |
|
VISUAL
colorHash
|
07006000040 |
|
VISUAL
cropResistant
|
6bc190c8e96be369,2c3be3679b6d6d68,b3363b3a20310346 |
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 334 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)