Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T103521DB9731011E09F0387DAFA2222FAE113817EDB5359DCD3644618B2D5DFD8955EC2 |
|
CONTENT
ssdeep
|
192:Qo8oB6CJ54t9jAF8JYbswv9vMtlku9cuGRmKbMpBXp7sfgg8gk:QRoCrJY5FvTsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf907582d5d095d1 |
|
VISUAL
aHash
|
ff81bfbf99818180 |
|
VISUAL
dHash
|
0d557d7979757963 |
|
VISUAL
wHash
|
ff81bfbf89818180 |
|
VISUAL
colorHash
|
06007000000 |
|
VISUAL
cropResistant
|
0d557d7979757963,78dbaaa294d9f4a2,a59c5a7565bab260,b7fdf969f1e1f167 |
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 490 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.