Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14A82D6E96BD4A3F8E006F3F4CB3565B67A1734FAB7528B90C2A45E94BA1445DC88DCC0 |
|
CONTENT
ssdeep
|
384:7m4N+9pq017jARzFTaru09XOMsuY3pZbnTJzeWBrH4XeB35/C136dUsUVLTlL/aT:7lVQVVIjbMWBUXEC1fLhFW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bd8ec339c0d26dc4 |
|
VISUAL
aHash
|
ff8f838f83838fff |
|
VISUAL
dHash
|
983e373c331b19c0 |
|
VISUAL
wHash
|
ff8f8183818186fe |
|
VISUAL
colorHash
|
06008000c00 |
|
VISUAL
cropResistant
|
983e373c331b19c0,fffffffffffffdfc,9b8e8ed340c1c341 |
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 241 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)