Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B6A2B634A41214A702B78DD4E874BF8E3AD6E70EC5EA95021AB883541FD7CF4F911AF9 |
|
CONTENT
ssdeep
|
192:npp3HfFKhwfeUjGg4RZwNilOAMY3mgJOWjNpfse:3HtKOiRZwN8fse |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
dac22d2f25ddd290 |
|
VISUAL
aHash
|
003cfc0000b0bf85 |
|
VISUAL
dHash
|
e7e9f9c1176c3555 |
|
VISUAL
wHash
|
707cfc0000b6bdfd |
|
VISUAL
colorHash
|
18006000040 |
|
VISUAL
cropResistant
|
d3d2d373636a88ad,e7e9f9c1176c3555 |
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 10 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.