Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D19194322101587B11338BE5F9D6F641C5E6E30EC217D8A4E3EE42EE2BE6DA0CC62535 |
|
CONTENT
ssdeep
|
48:TXTNIifTNg+spzdlDuaDwqa+N060B34In7kg45dnPKTnWnrDpmeFj0RIcJRZ5YEN:TzC5g+tU46Y7RGnWnEeFQRIgkEPT1ZOq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
88dd72ab542776e0 |
|
VISUAL
aHash
|
3c3c7c3c7c3c381c |
|
VISUAL
dHash
|
f0f0f0e0f0f1f1b0 |
|
VISUAL
wHash
|
3c3c7e3e7c3c1818 |
|
VISUAL
colorHash
|
00200030000 |
|
VISUAL
cropResistant
|
f0f0f0e0f0f1f1b0 |
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 27 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.