Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AB62C7F2D4011863022397C1F5A6BE4ED4BB934AD20D8C61E6BD029D0FD2DF47AA7876 |
|
CONTENT
ssdeep
|
384:eW1Z8KNMoMRAv64l/0ExKF9PMfK+wBnB5uur:eeZ8KNMoMRAv64l/0ExKF9PMfK+wBnBn |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c876e89b7388738c |
|
VISUAL
aHash
|
c0d09800180c1901 |
|
VISUAL
dHash
|
082424243a1ab313 |
|
VISUAL
wHash
|
f8d0dada1c1d1f03 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
0000104c4c081000,082424243a1ab313 |
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 27 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)