Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10FE1095393846947E133CBE9EB61CF54B22FA34AD38494A4F3F976E8E664D148CC4D48 |
|
CONTENT
ssdeep
|
192:j8w/iaLrI0VJfYXbrJfYXb/JfYXbHDyN0yki:j8oGbybGbH1i |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
965a19c84e73d966 |
|
VISUAL
aHash
|
3c3c2466767e7e3e |
|
VISUAL
dHash
|
70e8ccccccd4ccf0 |
|
VISUAL
wHash
|
3c242466767e663e |
|
VISUAL
colorHash
|
09c00018000 |
|
VISUAL
cropResistant
|
a282619696358aa2,70e8ccccccd4ccf0 |
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 1535 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.