Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A2D1B73061181E3DA1534779F670773861AFC34AEA4F981CF4AC1276DB8AC85D8236E8 |
|
CONTENT
ssdeep
|
96:TyDzKhcZkOPxK55dtmkwCAwLkwCABXBC7g9M893S2znGwvIXEfeo4NqI0tL:2DzKhAkNJXC89vBSonpIX+XYp0tL |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc66339966cc9933 |
|
VISUAL
aHash
|
0018181818181800 |
|
VISUAL
dHash
|
043032323232320c |
|
VISUAL
wHash
|
00db18db1818dbff |
|
VISUAL
colorHash
|
38000000e00 |
|
VISUAL
cropResistant
|
043032323232320c |
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 40 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)