Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13355037AEC0D5A09707675CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:YXfMQXhNSPGEqshNSBGEEhNS5GED6yML6Xw:YXfMQPj6yRg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e1641e5b1b39133b |
|
VISUAL
aHash
|
00e3c3e7f9ff83ff |
|
VISUAL
dHash
|
6907868f43432f0b |
|
VISUAL
wHash
|
00c3c3c3e9fd81f3 |
|
VISUAL
colorHash
|
06200008018 |
|
VISUAL
cropResistant
|
6907868f43532f0b,0418597939795804,458184e4249498ad |
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 50 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.