Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14A4219B4B62412A4CA0343DEFE2622FEA00351BEDA425BDCD3744249F299DFDC855DC5 |
|
CONTENT
ssdeep
|
192:QoyoBOJ5794E5bcM/7xcUu1y2cku9cuGRmKbMpBXp7sfgg8gk:QToUVcM/7xFey23smMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f7aa55aa55aa5488 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e6 |
|
VISUAL
dHash
|
4c4c4c4c4c4c4d4e |
|
VISUAL
wHash
|
c3c3e3c3c3c3c3c2 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
4c4c4c4c4c4c4d4e |
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)