Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15A32DFA0B058103672B392C870A9BB5B51E3F30ED54B1547A7E8632A4FC7DA9F678835 |
|
CONTENT
ssdeep
|
96:zMJwuZo1Q2hUaMAO1TyDzrpRutHop1BFD0bla9QFPYwuvMXY1bY7cYify0Adi5Tz:iaYp+ztRiy1Ebla9JMewIf3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b0ad4e9f184ee760 |
|
VISUAL
aHash
|
ffffffffffff0000 |
|
VISUAL
dHash
|
231c0e161e108cad |
|
VISUAL
wHash
|
00e7c7ffcfef0000 |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
231c9e1e169e1899,0000000606060400,0088ad88b08d8d29 |
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 5 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.
Pages with identical visual appearance (based on perceptual hash)