Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16E93995570A4606360B3C1FAD4B22F2E72CDF20BC61657B69BE40A8F6EDBDBC3510994 |
|
CONTENT
ssdeep
|
384:tVc6onGwuoUOoUkXdVHmjQkv7Wqa6aPRobxuvPRuPaiYkDMdZIQq+kcK25ll8lW/:tK6onG7ECq5am4RAbcK25T8UiLW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cb4bb4b4c6278768 |
|
VISUAL
aHash
|
ff99b939f8ffe7ff |
|
VISUAL
dHash
|
553b637111230716 |
|
VISUAL
wHash
|
bc093939f881c3e7 |
|
VISUAL
colorHash
|
07002000180 |
|
VISUAL
cropResistant
|
553b637111230716,44c30bd3d3dbab44 |
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 34 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)