Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11E41CE709CA51A7E5187C2D83BB9731F73E0C665CB81261199F8839E9FE7E02DE22254 |
|
CONTENT
ssdeep
|
24:hR/C+sLzGbhqKC/dNks6EyVFnMMrO1c6Rpn+nak1lc3vH7S1MQym3m923H6:TdqCbhqKeYs6EyPnMMyC6RBm1lCOh36 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a299dc2799cc6699 |
|
VISUAL
aHash
|
1f3f2767efe7ffff |
|
VISUAL
dHash
|
b56a4dcdcf4d4e8d |
|
VISUAL
wHash
|
070707070f073f7f |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
b56a4dcdcf4d4e8d |
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 4 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.