Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1078384319642D277831B47D8F7F4B312F2C24A5ECB53C8A4A5EE83BA63C9D90E961345 |
|
CONTENT
ssdeep
|
1536:+pL9iBZIIIQFK1JzKCp2yAKZI6FC+ff4U:7LyAZ6F |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
add6d52169693496 |
|
VISUAL
aHash
|
ffffff8101030303 |
|
VISUAL
dHash
|
9474280b0b0b0b0b |
|
VISUAL
wHash
|
ffffff0101030303 |
|
VISUAL
colorHash
|
3000000b200 |
|
VISUAL
cropResistant
|
c34767463218a43c,a236aaba2e4e6e8e,59516225a4227019,9474280b0b0b0b0b |
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 1222 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.