Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B8750807B395363E8643F0A06C8BCC59B739AA48228584AC655C90F86B5947CC77FFED |
|
CONTENT
ssdeep
|
49152:EQLasByM2Mof1uXuMmc8hqSo8xTTBM8qstfnpV0R8rvkmhbchbtMas:Nd8Alm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bb9560e842eb4e9a |
|
VISUAL
aHash
|
a39f9fff9fdbcf00 |
|
VISUAL
dHash
|
4f3e3a583c2b3b8d |
|
VISUAL
wHash
|
010f8fff8fc1cf00 |
|
VISUAL
colorHash
|
0e207000000 |
|
VISUAL
cropResistant
|
6f16385a5c3b2b3b,0000000000000000,54557be1e5211011,232b2b3b1b2dc7a5 |
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 228 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.