Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14ED2757872A116BF616B8BF9F1A2FB6594D5D34FC417D8A4E3FC93A607CAD909E02100 |
|
CONTENT
ssdeep
|
384:FkgoHRJ/J1EDInzX09X1Ne/VRttrtevWTv1prazeUbTeyEyj:qHRJ/J1EDInQB1NCpeqv1FAeUbTBXj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a49abc9b8e8e8e64 |
|
VISUAL
aHash
|
ffc3ffe7c3ffc3c3 |
|
VISUAL
dHash
|
299e240e8e618e86 |
|
VISUAL
wHash
|
ffc0fcfc003c0000 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
299e240e8e618e86,c023232b432320c0,c023230b032320c0,c020232b4b2323c0 |
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 38 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.