Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15BC3EA71612AB93B41E38AD8873A7E3E614BE351CB06D6C5A3E4834C9FC6CE0FD99154 |
|
CONTENT
ssdeep
|
1536:wuQQ4VX7wQp8hVFjjmjcu2bqJhdZ7zpRG:wPaZ8RjG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
807f7f0080ff80fe |
|
VISUAL
aHash
|
0000ffff7f7fffff |
|
VISUAL
dHash
|
c000c080a0a08080 |
|
VISUAL
wHash
|
0000000040404040 |
|
VISUAL
colorHash
|
0e000400030 |
|
VISUAL
cropResistant
|
0000000000000000,80d0a0a0a08000a0,80000080c0808080,0000000000000000 |
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 277740 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.