Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E9E229B4A230D335B1C24BE8DA6425287A5FE1DCD7C695B0F388AF15B0D6CE9D5260CB |
|
CONTENT
ssdeep
|
384:Y7bPhOJeguUT2RhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsUwRWiMd:Y7bPhOJeguzhhPhleMeDGCSPxeeWmHpW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3333fbc48301f4e |
|
VISUAL
aHash
|
00666070f0f0f470 |
|
VISUAL
dHash
|
5ccccac1a1a4a481 |
|
VISUAL
wHash
|
006662f0f8f4fef0 |
|
VISUAL
colorHash
|
30201000180 |
|
VISUAL
cropResistant
|
7370f1e19e94dcd4,5ccccac1a1a4a481 |
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 78 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)