Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12F621BB5E21513B09A4343EEFF2322EAF11340AD9A215BCCE778831DB1999EDC915DC6 |
|
CONTENT
ssdeep
|
192:QovoBOJ5794uaPw7FcDfNJXOED9Gwn4lku9cuGRmKbMpBXp7sfgg8gk:QCoUfF+NJXTpznjsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
952a552a55aad5ab |
|
VISUAL
aHash
|
03033f073f3ffffe |
|
VISUAL
dHash
|
4645616d6c760f3a |
|
VISUAL
wHash
|
03003f070fbf07fe |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
4645616d6c760f3a |
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 491 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)