Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12A243BB87119B12A5AB307B740BF1403B678123B5C0D8C70A364E95EA2FDD9DA46BFD4 |
|
CONTENT
ssdeep
|
3072:BSPQ5dgn7148CJ6qeaaUxWUQwlrX2wd9W/guGO+:Qo0n541J6N+Wp6r+ouGO+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d3332cc5ed2c3493 |
|
VISUAL
aHash
|
022c2c6c7c7c3c00 |
|
VISUAL
dHash
|
96c9c8d8d8d8e869 |
|
VISUAL
wHash
|
422c2c6c7e6c7e3c |
|
VISUAL
colorHash
|
300010000c1 |
|
VISUAL
cropResistant
|
61f1f0c4c4687021,9d7939ac8ccececc,cce49bd9d9d46667,96c9c8d8d8d8e869 |
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)