Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1909101716101A8575112E3D8B270D75FA3C68386D7479A0523FAB3AE26CBDD4CC660EA |
|
CONTENT
ssdeep
|
48:TqMuCQmcHC1lSANmApYRPOQMe9/VmbWvpeMyO2If5tnuBw0OZ2kZEhTuT:ToAvhNKRWQfZ8bSyO2IXu2T |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fd69405e4f4b1a1a |
|
VISUAL
aHash
|
00c3ff819dffffff |
|
VISUAL
dHash
|
101633337b300000 |
|
VISUAL
wHash
|
00c38381019fffff |
|
VISUAL
colorHash
|
07000038000 |
|
VISUAL
cropResistant
|
1716231379140100,1050505010105010 |
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 25 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.