Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16D03952412082E3E661386E1F795F3BD607DE385DA1A940CF17D02E26BD6CD8A47B7E4 |
|
CONTENT
ssdeep
|
384:0uXEJsD87R2SjZejGjnSbNZp2NZpLNZpnNZpd2NZp2NZppjzIsAR32qBNY+ninmj:0QTD87R22ZKi0SNJYSpcDsuyi7Z86n1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b36666666666cc8c |
|
VISUAL
aHash
|
e7c3c3e7ffffffff |
|
VISUAL
dHash
|
4d4d164d2a323210 |
|
VISUAL
wHash
|
0000000038381818 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
4d4d164d2a323210,a2a08ab2a282c0e2,c28cacf2b2b2a2a0 |
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 59 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.