Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E25211716028EE33929791EAA5F2835F31A2C74ACE572301D7FC93E90BC6CE4DD19496 |
|
CONTENT
ssdeep
|
192:rAFpPH16HBfzKuEhAmkBJ6VGcTUUZyIMYee5KxplIxvDJ:ULPV6hL1iheMl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3996c6699993299 |
|
VISUAL
aHash
|
ffffffffe7e7ffe7 |
|
VISUAL
dHash
|
000012324c4d324c |
|
VISUAL
wHash
|
ffffdfdf18000000 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
000012324c4d324c |
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 33 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.