Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16F82F872219117BE109787E8F2D0B72C5166B61EF963A845D38F022A6FD2DE7CC781C8 |
|
CONTENT
ssdeep
|
384:OGuHt2DVKhcXbEDSBKBBu+NAGOM3G0gTJ5NlqW:OGuHt2DV0hWqjNApMeJ5NAW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3e3cc1c38c3333c |
|
VISUAL
aHash
|
ffffe7e38183ffff |
|
VISUAL
dHash
|
80004c0e2b2b00a0 |
|
VISUAL
wHash
|
33b365018181ff7e |
|
VISUAL
colorHash
|
0700b0000c0 |
|
VISUAL
cropResistant
|
80004c0e2b2b00a0 |
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 711 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)