Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16582DC74DA50243A82235E9770F2574D72DEC10ACD076C814BB893E7DBC7E917816BAE |
|
CONTENT
ssdeep
|
192:RSZnGQUHxb1QH4yb1QH4yb1QH4yb1QH4ybPhvgfs/EwMnwMvxl58wMvxAwxu8V89:04HNSHTSHTSHTSHTPhvgFpZlKZNkZNyI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e0d786b2f292a7b0 |
|
VISUAL
aHash
|
ffc0c0c0c0c1c1c1 |
|
VISUAL
dHash
|
cc02120113139383 |
|
VISUAL
wHash
|
ffe0e2c0c0c1c3f3 |
|
VISUAL
colorHash
|
000010001c0 |
|
VISUAL
cropResistant
|
cc02120113139383,71ccdaa6a6decc70,3f78c08185c1783f,658eb32929b3ce68,78e2ca87b1b09193,0006215547470616 |
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 1093 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.