Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T121D22861A50295A282F798C2D9737F1E72D7F30F8066CB056ABC81AD0FE3CF5B515A60 |
|
CONTENT
ssdeep
|
384:vYLPzYL3QMvGM1CF98FcZFbfFFiFOAqFDAOFgccX1H14SmrBZcHIiNSiqI53Q6lg:vYLPzYLCMs6S5QOTDRH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3336699999989cc |
|
VISUAL
aHash
|
e7e7e7efe7e7e7e7 |
|
VISUAL
dHash
|
0c0d0c1c0c0c0404 |
|
VISUAL
wHash
|
0000000cc0c0c0c0 |
|
VISUAL
colorHash
|
070010080c0 |
|
VISUAL
cropResistant
|
0c0d0c1c0c0c0404 |
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 25 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)