Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DF72C7A493C85E3EE40783D5EA71373823BA5097E64A0134C5FD9BB85F42D8CE82B5C9 |
|
CONTENT
ssdeep
|
384:6doPY+QIIguyQzD+kSjm7EOC2C65DfRldbhz1bJ:6doPYyzQzD+kd7NC25ZR3fJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d2ed6db492c125e4 |
|
VISUAL
aHash
|
6280646c76444000 |
|
VISUAL
dHash
|
c627cdc9cccd9b84 |
|
VISUAL
wHash
|
f2f3f57c7e644000 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
be70e1c287c3e13c,c2e13c1abc70c182,c627cdc9cccd9b84 |
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 29445 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)