Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BF63FDB091226219816FA1D1F0519BDEF263931AF717480C97EE3B57E3DECB018A25ED |
|
CONTENT
ssdeep
|
1536:Av6vzuSr9XI3MyiTicXoJnv6vzuSr9XI3MyiTicXoJ3s5:Av6vzuSr9XI3MyiTicXoJnv6vzuSr9Xr |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc999966cc66cc66 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
3232303030303032 |
|
VISUAL
wHash
|
383818183f3f1f1f |
|
VISUAL
colorHash
|
38000000e00 |
|
VISUAL
cropResistant
|
3232303030303032 |
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 29 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)