Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AB04627C3102159B6133CAC074A1BF1AF0A2F30BDE6AE505D5EE12559FCFC62A9E8674 |
|
CONTENT
ssdeep
|
1536:X0DHZ3xhC2vEzByikpqm84dIdxAdk43aaiyav1t4tBaR1Vp/7FUZL8RpX4:cHZ3xhCuEzByikpqpiIdZ1hUZL8RpX4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
89ae33f388a688dd |
|
VISUAL
aHash
|
e700191918180001 |
|
VISUAL
dHash
|
4f2b33b333b055b9 |
|
VISUAL
wHash
|
ff981b1f181c191d |
|
VISUAL
colorHash
|
31208008240 |
|
VISUAL
cropResistant
|
f0f9c2c2d2ae6ce2,4f2b33b333b055b9 |
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 62 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)