Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T106929932E100527302B399C8E6B9BF2EB692F30FC917D6106EAD41D51FE3CB4B8655A5 |
|
CONTENT
ssdeep
|
192:66VREnXMO2vCcClCvF7FFFIFOuFDVbTmGGoqhZZ9/tD:ZeXMBTY8F7FFFIFOuFDsD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33366cc89cccc99 |
|
VISUAL
aHash
|
e7c7e7e7efffffff |
|
VISUAL
dHash
|
4d4d4d4c48141044 |
|
VISUAL
wHash
|
c0c0c0c4ece4ece4 |
|
VISUAL
colorHash
|
07008000e00 |
|
VISUAL
cropResistant
|
4d4d4d4c48141044,0101010501010206 |
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 22 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)