Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19ED2C7FC505011BA9127EBC2F3746F29F1E2B35ACF258740A7FC83504AD3E616A6E529 |
|
CONTENT
ssdeep
|
768:bUHRyfdD2q8Eq3eNnnrMGryxVwb8L1Zb1CYdjUdzs3HcrIJz2dbfUulFUodhY9za:RodJ2dndTxSQcGtIK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9ba564dadae5901a |
|
VISUAL
aHash
|
ff83ffff3c180000 |
|
VISUAL
dHash
|
002b92f8797986f0 |
|
VISUAL
wHash
|
ffc3ffff3c000000 |
|
VISUAL
colorHash
|
0b0000001c0 |
|
VISUAL
cropResistant
|
83e5e100aaaa0210,80181e06a0dbdba4,b07083646071d4e0,329aca7979c686f0 |
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 5 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.