Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FAE229B4A2309335B1C247E8DA6425287A5FE1DCD7C695B4F388AF51B0D6CE8D8260CB |
|
CONTENT
ssdeep
|
384:Y7/t2utTyoRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AscSRW+Md:Y7/t2uk2hhPhleMeDGCSPxeeWmHbW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3383f9e6eb108c9 |
|
VISUAL
aHash
|
00666060f0767660 |
|
VISUAL
dHash
|
5cdcdac3c3ccccc1 |
|
VISUAL
wHash
|
806660f0f0f6ff70 |
|
VISUAL
colorHash
|
30200e00000 |
|
VISUAL
cropResistant
|
81b0e170f4ecf0d8,1008323232080000,5cdcdac3c3ccccc1 |
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 72 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)