Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18F03FB317100512B5AB3D6C4F5A17F4FB2A7E30FC60A85682AF9419A1FD7EB6B811E70 |
|
CONTENT
ssdeep
|
384:wp5gLpHuVsa44pDov8HifhoLZuJYkZTKyPCA4c3fL:wp5ZsopDoSiJoLZuJYklKyPCA4c3T |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
af2e13116a66633d |
|
VISUAL
aHash
|
009f91919bffffff |
|
VISUAL
dHash
|
8b34672732447213 |
|
VISUAL
wHash
|
0093819181bfb7ff |
|
VISUAL
colorHash
|
072080080c0 |
|
VISUAL
cropResistant
|
2c376727324c720b,01063b8bcbaba744 |
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 32 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)