Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14A34E9B4B150253A636712D8A125B34AE287F34FEE570ED4A3BC87D26BD7CE48C27494 |
|
CONTENT
ssdeep
|
3072:ElJlRlgXllgYslnlXlclxOlclUxQZcnJQNsHvNqM3lsu3AYBhy5N:9EQZcnJQNsBLY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bc38674367536c1c |
|
VISUAL
aHash
|
00df9fdffffffff3 |
|
VISUAL
dHash
|
4330371713230006 |
|
VISUAL
wHash
|
008b8b8193f9ffc3 |
|
VISUAL
colorHash
|
070c0000080 |
|
VISUAL
cropResistant
|
4330371713230006,058a723333720211 |
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 683 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.