Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A422F6F8722404E5EE03D7DBA922327AA003917FEE5256D8D3688758B299DFDC850DC6 |
|
CONTENT
ssdeep
|
192:QoMoBZJ5I9+sMu9cuGRmKbMpBXp7sfgg8gk:QLoWWsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e62ed19957267489 |
|
VISUAL
aHash
|
f3ff93b7fffffffe |
|
VISUAL
dHash
|
a4d4256549314148 |
|
VISUAL
wHash
|
102094b4fcbcfcfc |
|
VISUAL
colorHash
|
07008000e00 |
|
VISUAL
cropResistant
|
a4d4256549314148,0f3f1f3f7f767f3f |
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 487 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.