Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T162E309306181237F097701DDB278FBD6D3DEE21AE332455571DC82AAB7C2C60AA37999 |
|
CONTENT
ssdeep
|
1536:VK2TdInvC0CIJ/dl36q5o077X4O5FI7/TM5n4krFWkcr9YKrUwrpfe3t:VK2Tdetbjpued |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
978d4935b72521b5 |
|
VISUAL
aHash
|
5a3c1c363e00183c |
|
VISUAL
dHash
|
b27171cc4c4d3271 |
|
VISUAL
wHash
|
7e3c3c7e7e00183c |
|
VISUAL
colorHash
|
380020001c0 |
|
VISUAL
cropResistant
|
b27171cc4c4d3271 |
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 192 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)