Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EAE228B4A230D335B1C24BD8DA6425687A5FE1DCD7C695B0F388AF11B0D6CE9D9260CB |
|
CONTENT
ssdeep
|
384:Y7bPhOJeguxTuRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsswRWOMd:Y7bPhOJeguWhhPhleMeDGCSPxeeWmHJW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f02317fc6e034b4e |
|
VISUAL
aHash
|
806660f0d8dede10 |
|
VISUAL
dHash
|
5cdcda93b1b4ac21 |
|
VISUAL
wHash
|
80466ef0d8dedf90 |
|
VISUAL
colorHash
|
38001000c40 |
|
VISUAL
cropResistant
|
b62c69c89081020c,5cdcda93b1b4ac21 |
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 74 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)