Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T168E2EA316841DC2A01DF99C99133522A61FA8345C62316CAFAB5C7F9ABEFC3DDA37114 |
|
CONTENT
ssdeep
|
768:rsIx/jteeezeeeeeee2ZuYL+fUf7Cd4yWG2w:rsIxpeeezeeeeeee2ZB+Q79y8w |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b121f862f4e574a5 |
|
VISUAL
aHash
|
c20d07070700ffff |
|
VISUAL
dHash
|
9419deeececd3b3c |
|
VISUAL
wHash
|
c30f03070700ffff |
|
VISUAL
colorHash
|
33c00000000 |
|
VISUAL
cropResistant
|
a0a080d0c0d09090,0408080a08080901,0281c1c4c0606460,c666b6bedad8ca8c,e0e0e24040c6eee0,1f003d383e3e3c3c,96995bceeedecd2d,e9c9c9d9d1ededf5 |
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 41 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.