Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FAE1653029205A2F27178BB4B56173A9A18AB34FC547CC15E1FC066BAFDAEE1D933560 |
|
CONTENT
ssdeep
|
96:TGmpMB4kBv/U2Jasvy0okCAGkCiPabdHQ4WA87HEW98YTUoIH47kx6oDX6K7ul1F:ampMBZReJaJ7T9/TABjy9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a37e0d6631d89936 |
|
VISUAL
aHash
|
00e7e7efe7ffff5a |
|
VISUAL
dHash
|
160e080c4d08c096 |
|
VISUAL
wHash
|
00e7e7e7e7e74200 |
|
VISUAL
colorHash
|
07200000c00 |
|
VISUAL
cropResistant
|
160e080c4d08c096 |
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 22 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)