Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C8837BB2A6CD1C9F3B83ACDA5C257F60D482D231F58E0798E9E5591D0EC2FD4B482366 |
|
CONTENT
ssdeep
|
768:EVuK1BsPco03UjUgUBHUVIUVYUUrO7vjw1b:s330XexGGX |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e969979696969096 |
|
VISUAL
aHash
|
ff8181c1ffffffff |
|
VISUAL
dHash
|
3303032320171216 |
|
VISUAL
wHash
|
df818181ff8383e3 |
|
VISUAL
colorHash
|
07000438000 |
|
VISUAL
cropResistant
|
3303032320171216,0000808000800000,0100000303000000 |
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 30570 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)