Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T184E23AB4A230D335B1C24BE8DA642568765FE1DDD3C695B0F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUWeguITkRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsESRWwMd:Y7fUWeguthhPhleMeDGCSPxeeWmH9W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c4333fbc68984b78 |
|
VISUAL
aHash
|
00206070f0f0faf0 |
|
VISUAL
dHash
|
4ccccac181c4c4e5 |
|
VISUAL
wHash
|
806660f0f0fcfef0 |
|
VISUAL
colorHash
|
31e00008000 |
|
VISUAL
cropResistant
|
b261e4e4b2b3a969,80100c4c4c081000,4ccccac181c4c4e5,c7e68657872d3932 |
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 73 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)