Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B922D83612501E7F5A03C688F6D4B319A79FA257C677D849B1EC835B23D2E21DD231B8 |
|
CONTENT
ssdeep
|
192:8XO6uEkEkX2XS445iPxOYs4YgAlXU1jRXVRXJWYThkkXGXXpRDeJW:5gxOYVYkjRXVRXJWYqJXDeA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3b34c990de44ce6 |
|
VISUAL
aHash
|
0effe7ffffffff00 |
|
VISUAL
dHash
|
da1c0e189d140e20 |
|
VISUAL
wHash
|
00c7c3ffc7cfc300 |
|
VISUAL
colorHash
|
06007000000 |
|
VISUAL
cropResistant
|
c2180e0e1c16160e,2000606008600020 |
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 8 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)