Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1223284B1229716BF720B47C0B0169BBAF0A9C78CC787596872F942B557E3C84DC5A392 |
|
CONTENT
ssdeep
|
192:xAMeCMk5zg1+wOVRg+VRGY5GC5GUqIP9lVpSo:1Mk5zg1+wOPHvGY5GC5GUrbpSo |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d333866c2c6fc1c3 |
|
VISUAL
aHash
|
006c6c4c4c40387e |
|
VISUAL
dHash
|
d8d8d999d098e8d4 |
|
VISUAL
wHash
|
606e6c4c5c4c7c7e |
|
VISUAL
colorHash
|
30001000180 |
|
VISUAL
cropResistant
|
ac6464322622c894,d8d8d999d098e8d4 |
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 304312 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)