Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T130020531F014783B15B759FAB964EF0AB1C7E206CE170A8E76FAD2890FC7D1ADA15160 |
|
CONTENT
ssdeep
|
192:irt0MqnCHzMj7CRMMkC2iHgRWoNTMUNvNpUuUjUAUNBDAZ/KzUDmU9Uj:irbNxvgoylnBDAg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
989967e6e0669e98 |
|
VISUAL
aHash
|
ff1f1f5f5f0f0000 |
|
VISUAL
dHash
|
d0f4f4b0b035c9f0 |
|
VISUAL
wHash
|
ff3f1f5f1f030000 |
|
VISUAL
colorHash
|
17680008000 |
|
VISUAL
cropResistant
|
f0f8f4f4b494b4b4,b2787c3c7179f3e2,afc69393d7423496,b03288a8c8f130c0 |
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 12 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.