Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T125821CF4C28564BB515381C59B327F29B3D24148C3221A45ABFDC38EBB89D66FE33618 |
|
CONTENT
ssdeep
|
192:qfVq84/imJOgUt/9MJWXWbfVksb8VbEUmyEOpGKGFZq5jd:d84qLuJWXWlqbwzq5x |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bde6d898672cc0d8 |
|
VISUAL
aHash
|
fffff703031f0f0f |
|
VISUAL
dHash
|
ce7026664e30b036 |
|
VISUAL
wHash
|
ffff0303030f0f03 |
|
VISUAL
colorHash
|
0f000200081 |
|
VISUAL
cropResistant
|
ce7026664e30b036,59a5a4532c8ccc3d,81c0c4401cacac31,7ea6a4bc7a444464,4541010101010101 |
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 878 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)