Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C823D43102022A3B12276AD5B560FB68D4D7E34CEB97D90CA3FD41973BE7CE04E9A165 |
|
CONTENT
ssdeep
|
1536:tPCOGEcEnEpior5R2DCQkeBQfMrwdcYItaKaNI1rm:tJor5R2DCQkeBQ6gKT1rm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
96ca68617b6bb688 |
|
VISUAL
aHash
|
013c3e0c2e2e1c9e |
|
VISUAL
dHash
|
0df0646854547074 |
|
VISUAL
wHash
|
813e1e9c2e2e3c9e |
|
VISUAL
colorHash
|
30202000080 |
|
VISUAL
cropResistant
|
ffaff6b4f0f6e4ec,2832c8cce7a6fcd8,0df0646854547074 |
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 172 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)