Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16AC2423096585923619BC0D4EA629B9F3356C382C31307697BF4D276FACECA1CD725CA |
|
CONTENT
ssdeep
|
384:hvtuRQH9o2HmOw5QT0N7p+XuW7aq9jg6bRWKZ:hVhH2kVZIKZ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc7c33c8cc7333c2 |
|
VISUAL
aHash
|
801800181818603d |
|
VISUAL
dHash
|
113010303232cc61 |
|
VISUAL
wHash
|
d918181818187e7f |
|
VISUAL
colorHash
|
38006000080 |
|
VISUAL
cropResistant
|
113010303232cc61 |
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 261685 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.