Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C5C3D9301100303F1AFBAAEC71D5FA81929FC698DDE5648DF3CC85A517CAE64C9DAB91 |
|
CONTENT
ssdeep
|
3072:D4ZaQ/emc/emP/em8/emKlt/emc/emP/emd/emuQjAdXCXqXlmabmajmaQmaNa7N:6aQmmcmmPmm8mmKPmmcmmPmmdmmuQUdz |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c1b64a9dcaa76227 |
|
VISUAL
aHash
|
ff6e667e7e7e7f78 |
|
VISUAL
dHash
|
41d2ccccd4dedad1 |
|
VISUAL
wHash
|
fd08263e2e7e2a68 |
|
VISUAL
colorHash
|
07001000e00 |
|
VISUAL
cropResistant
|
41d2ccccd4dedad1,912cae3496212080,1666661667032627 |
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 351 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.