Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FCC1B9711148083FA62382F5F9E1F74A90E9C319C55BDA54E3ED01BA2BCAD85DC376B4 |
|
CONTENT
ssdeep
|
96:TlDnY8A46Yb4tHWkmBfY6H6cIK5k1MBm7IGBEAG1QXNI1y:/vp7GGm9IE |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f8b00f0fec2d4ccc |
|
VISUAL
aHash
|
01cdc0c3f8d00010 |
|
VISUAL
dHash
|
1999969680b16263 |
|
VISUAL
wHash
|
01cfcfdbf8d81818 |
|
VISUAL
colorHash
|
17601002000 |
|
VISUAL
cropResistant
|
1a12722e31300e0e,1999969680b16263 |
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 32 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.