Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T162E239B49230D335B1C247E8EA6425287A5FE1DCD7C695B4F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWegulTJRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsUYRWeMd:Y7fUWeguFhhPhleMeDGCSPxeeWmH9W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c13f3fcce838384c |
|
VISUAL
aHash
|
00206070f0f0f470 |
|
VISUAL
dHash
|
5cdcdac3c1c4ccc1 |
|
VISUAL
wHash
|
802660f0f8f6fef0 |
|
VISUAL
colorHash
|
32201c00000 |
|
VISUAL
cropResistant
|
b273c1c8c0ccc8d8,1008323232100800,5cdcdac3c1c4ccc1 |
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 75 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)