Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D4831AA43949F5271AB343A760EF14037278122B580D4D20B254ED9EB6FDC9AB07BFD9 |
|
CONTENT
ssdeep
|
1536:jcowLUZlUuRNka2wblHbJLwLIz9GguGOjjRnK:bRrX2wd9W/guGO4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eb4117594fd14b49 |
|
VISUAL
aHash
|
00e3f3ffd0d8ffbf |
|
VISUAL
dHash
|
c12783f533b25069 |
|
VISUAL
wHash
|
0083e1ff80c8ffad |
|
VISUAL
colorHash
|
06601008000 |
|
VISUAL
cropResistant
|
800080c2c2c20080,a707a331b3b25169,a2bab2b2aab5b1b1,c1d1c1d11ce46607,6c6f4949250d4989,0f5949696975750f,cacfccccc5c70353 |
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 47 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.