Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T160B19662D704053B1D6375CCF76D3F4AE6E3928BEE1A580620AC52481FDBE6CDD622E1 |
|
CONTENT
ssdeep
|
96:y+vPgx2uoplEbrDH7/tB1J0m211OOMWf0ddqhH0HahfA:PHgxaplWr7rr1Kme0L+H0HahfA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e664cc989b993363 |
|
VISUAL
aHash
|
f7e3c3c7e7e7efe7 |
|
VISUAL
dHash
|
26060e8e4d0e0e0f |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07440000003 |
|
VISUAL
cropResistant
|
26060e8e4d0e0e0f,4f4dd69733341c1a,6090906090906000 |
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 6 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.