Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AFE11E38BD8475B7608781F5B2A15F5EB3C48107C727A664F3F5A3888B8BC36CD84685 |
|
CONTENT
ssdeep
|
96:5RpnY1N4TQvQKuiJeSMzAdyNc7JHrGPPbkcxz2PTeiwDsK73Mr/x/BDXgtHnPJZI:DTXUDY0JlYTDj3BXdM |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92656d93b4b69269 |
|
VISUAL
aHash
|
02006e0e0e0e0000 |
|
VISUAL
dHash
|
9653dcdc9c9cb976 |
|
VISUAL
wHash
|
e6c0ee7e6e4e0c18 |
|
VISUAL
colorHash
|
310001c0040 |
|
VISUAL
cropResistant
|
7c616dcec6ceecc0,9653dcdc9c9cb976 |
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 128381 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)