Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T139C25465F60038BB813BE7E7FA517F24619EF347D4664984CBA483940FD7FA0E922462 |
|
CONTENT
ssdeep
|
384:sL4HQh8t7MqU+29ctda9TJCuiUL/y3UnZ1lO:vE8t7MqU+29EQJCtUnZ1lO |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8dada9a9a9a1a3a9 |
|
VISUAL
aHash
|
1b18181818000000 |
|
VISUAL
dHash
|
3330323232100000 |
|
VISUAL
wHash
|
9f1f1c1c1c0c0c0c |
|
VISUAL
colorHash
|
07600030000 |
|
VISUAL
cropResistant
|
82152c0de2c48030,3330323232100000 |
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 187 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)