Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F962B9A96349077B637B00F4B5619BD4E16DFB8CCB174D84B3EC80A2578EC518E75B88 |
|
CONTENT
ssdeep
|
384:fYNur+HyvJvULTn4T1JVmuaEUJL6eoaAzh31++lxQ5m7vl:ANueIxUDAnVUJ2lTIm7t |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d9d86266cad8d872 |
|
VISUAL
aHash
|
00003c3c7e3c0000 |
|
VISUAL
dHash
|
31e4f0f0f0f0e070 |
|
VISUAL
wHash
|
80387e7e7e7e3c00 |
|
VISUAL
colorHash
|
38000600030 |
|
VISUAL
cropResistant
|
5a6b63eaea62c949,22264a9a8acadbdb,b8c96d09985921b9,31e4f0f0f0f0e070 |
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 243 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.