Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E0128732120C5F7DB653CAE8F6A5B338466ED24ED65E8658E6BC02B257C3C45C433698 |
|
CONTENT
ssdeep
|
192:smMdNyjAMEQyvfgVeB80qCXVgOFjb3p8jp:pMSlIB8kXCOFXKjp |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e54c4c64f2dae2e2 |
|
VISUAL
aHash
|
0000ffffffffffff |
|
VISUAL
dHash
|
17320c084c4c0c4c |
|
VISUAL
wHash
|
000000e7e7ffe7e7 |
|
VISUAL
colorHash
|
07000000007 |
|
VISUAL
cropResistant
|
884d184d0c0c084c,0f17161632b2f2d6 |
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 11 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.