Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FB11AB3040858DA762C1EBE85771562E76C2D647DF871F4952F083AD6FE2F49CD02182 |
|
CONTENT
ssdeep
|
12:hRwMy7FUEcxjApkxah9oGgAZ3oJD9kDVgCWgxQu4q5KCaDENMS7pd+sPw:hR/CFfSxHBAZYN9uuVmak7K5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce2331cc3338cec7 |
|
VISUAL
aHash
|
0000303838300000 |
|
VISUAL
dHash
|
0060646060642000 |
|
VISUAL
wHash
|
00303c3c3c3c3000 |
|
VISUAL
colorHash
|
38401000080 |
|
VISUAL
cropResistant
|
a3233831316b787b,103c2c28e22e3766,0060646060642000 |
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 13 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.