Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11F739230B400DA3341E785D5A236E72A63A24305C65396D9FFF583F687EED68CB63219 |
|
CONTENT
ssdeep
|
1536:iHEmuM2c+s2R6ExLqUDnNRx7qMiiLcgjhwI1HscE84RaW6RZpD86NKYEk7v:RdM2c+foMitcE84RaW6RZpD86NKYEk7v |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e196bcd4afc1a81c |
|
VISUAL
aHash
|
ffff002000000081 |
|
VISUAL
dHash
|
802981c3c1c0d20b |
|
VISUAL
wHash
|
ffff41e0e0e0c0c1 |
|
VISUAL
colorHash
|
32407000000 |
|
VISUAL
cropResistant
|
81810c03c3c80000,2993c3c380c21a0b |
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 279 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.