Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19CF1A56021011A2F332B99D5F215A3A9D0DBA70EDA27D839A27D037B07DEDC0FD65E81 |
|
CONTENT
ssdeep
|
192:QPuPpuj4VDcNyXLHZhonQkeaGrkpSn23+kO7Nb:D0ne1I3pg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
97931d17864d8cf2 |
|
VISUAL
aHash
|
3cffffffff0000ff |
|
VISUAL
dHash
|
f0c8154c08110800 |
|
VISUAL
wHash
|
00cfe7e7e70000ff |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
70dc1b4c144d4d16,0000000000000000,0001000b0b000100,0040404040404000,0000004000014044 |
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)