Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16952B62511556E3F6523CBF9F2A1F361C2A9E36ED27BCA19F2EC036227C2C51C992354 |
|
CONTENT
ssdeep
|
192:UPNCNnNeNDNP3vTgqvV4lWYBqoHaYBKSjSYokPtL/9YCA:UlyN+5jgqgWYXaYnSYowYCA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9c49beb26138e31b |
|
VISUAL
aHash
|
0000000000ffffff |
|
VISUAL
dHash
|
1432b232680c2a2a |
|
VISUAL
wHash
|
00000000ffffffff |
|
VISUAL
colorHash
|
031c0000000 |
|
VISUAL
cropResistant
|
100c32323232b230,218292aa9692a282,14004c0c322a2a2a,0010101010100000,3230303232283200 |
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 562 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.