Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133730F42D475012B002BCBF5F19713F824DE11F9EA4649E5CAA8A2E777D9E90F487F0A |
|
CONTENT
ssdeep
|
1536:w/5ekVvkG4dFkO2Fq3Wgvv536SzDRx759R4ZTlTUV:w/7G |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b067745c47584757 |
|
VISUAL
aHash
|
000047ffffdfdfff |
|
VISUAL
dHash
|
869794aab2b0b4a2 |
|
VISUAL
wHash
|
00000050ffdfdfff |
|
VISUAL
colorHash
|
07e00010000 |
|
VISUAL
cropResistant
|
0100000000000000,96958caaa2b0b4ea,8003808080a2518a |
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 42 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.