Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DE24A721720C3E7DE50B8B9CF3A0F376527AD195EA2A912CF2B911312787D89DC67784 |
|
CONTENT
ssdeep
|
1536:Kvwdm6NaGmB8zlJlg9f1xvLP5DFtnN6aOHXnaQGn2LEfcccc4qfccccCfcccc6fX:4yr015qII2W9fFq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
90cbee6ec993c291 |
|
VISUAL
aHash
|
ff000e6e66000e0f |
|
VISUAL
dHash
|
c59e98d8dc859c9a |
|
VISUAL
wHash
|
ff000e6f6e440e4f |
|
VISUAL
colorHash
|
020000001c0 |
|
VISUAL
cropResistant
|
0009414949a1018a,c09113515d71f8ae,cd04c02e2ce5848c,c798d8d8c4859c9a |
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 38 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.