Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C081BC2074506A1B4623AFC0F9E0EFC56EC3E36DCD0A9560D7AA46EE1FD3DE29914871 |
|
CONTENT
ssdeep
|
48:I4fupYDQge3aohaztW9AxaNlKr+SBfQNLJSjqyCg4sVhhHWWYF1UzW:vu1cEafQ1JSjqyC1sV3Y/UzW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3cc9930669b8c67 |
|
VISUAL
aHash
|
e7e7ffe7c3c3c7e7 |
|
VISUAL
dHash
|
0c0c000c4d145d4d |
|
VISUAL
wHash
|
c300fce4c3c3c3c3 |
|
VISUAL
colorHash
|
07000038000 |
|
VISUAL
cropResistant
|
0c0c000c4d145d4d,1771c0c4e7c07133 |
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 316 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)