Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F40343735501643B432367CDB0227B5EE193831ECE9708A8F2FD8B971BE2DD99919C1A |
|
CONTENT
ssdeep
|
768:KXZkvhtQIn+f35cPcy8k82eIICx0KR3SUyzjT2SlSUyzjd1/y7KJrInEnaz8+1Gl:KXZkvhtQIn+f35cPcy8k82eII5KBSUy6 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ad52a93b5ca7a152 |
|
VISUAL
aHash
|
007070121003031b |
|
VISUAL
dHash
|
06e0c4e4b49307b3 |
|
VISUAL
wHash
|
e37874767073031b |
|
VISUAL
colorHash
|
380c0006000 |
|
VISUAL
cropResistant
|
804b726971710c14,06e0c4e4b49307b3,016928174d30b10d |
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 815 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)