Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12D13A6BA2201166F012B82D5B161FB9FF06BD745CE63DD0EE3EC51C26BCBC548D91661 |
|
CONTENT
ssdeep
|
384:x216P3Yb1SWMOZ9vafg/C2OuOPiFNO3rSUiSg0XAtuLWJoCJs4vTh+0+OjlX:1fYb5dCGMg0OSCO4vThbLjR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8976ae22aaab7a8c |
|
VISUAL
aHash
|
9918181818181919 |
|
VISUAL
dHash
|
29327272b3b0b333 |
|
VISUAL
wHash
|
bfbe383838181b99 |
|
VISUAL
colorHash
|
3100001000b |
|
VISUAL
cropResistant
|
29327272b3b0b333 |
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 270 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)