Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C1E201B092A58D7700AFE1C6A770BF4F72F2D299D9A3460207F897685FDBC84EC02955 |
|
CONTENT
ssdeep
|
768:FJQx85wVMTAzhZzCJNJz61zz8vzJCzua72zCW3zCPcb1lTaHSQRwFUbL4cu1L9YB:E8CoYCe1eqDy2ueHeDwVCS839/PnS+Ly |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed4d46329271694f |
|
VISUAL
aHash
|
00fbfbffff81c3ff |
|
VISUAL
dHash
|
4d26121a601f1f43 |
|
VISUAL
wHash
|
0083fbebbf8181f1 |
|
VISUAL
colorHash
|
07400010200 |
|
VISUAL
cropResistant
|
0632121a201f1f63,0003034b4b430300,b8f8d836258fd3b0,00448c3cf4d409a5 |
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 16 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.