Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C4932AB43A58F5665AB3439710EF2103B379552B540E4C20A354ECAE72BCC9BA077FDA |
|
CONTENT
ssdeep
|
1536:iBMXPvbpWpFo2h20VTgHd8tVPTMnEXCd0uq+wSRKF:iBMXspMug98nKd0+w1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b13e1c1c1e6c5c76 |
|
VISUAL
aHash
|
00efc3e7efffe7e7 |
|
VISUAL
dHash
|
31980e0c1c108e0c |
|
VISUAL
wHash
|
00c7c3c3c7cbc3c7 |
|
VISUAL
colorHash
|
06007000000 |
|
VISUAL
cropResistant
|
31980e0c1c108e0c |
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 13 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.