Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10A5219B9732411A58A0343EEFA7762BAF113826EDA621B8CD379435972D5CFDC820DC5 |
|
CONTENT
ssdeep
|
192:QoMoBZJ5I9j200sIbAp0q5R6xDhbfdDMu9cuGRmKbMpBXp7sfgg8gk:QvoW7fTT5RehZIsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf4ac025d56ad08f |
|
VISUAL
aHash
|
ff818181838381ff |
|
VISUAL
dHash
|
51694d4d06064f54 |
|
VISUAL
wHash
|
ff818183838383ff |
|
VISUAL
colorHash
|
32402018000 |
|
VISUAL
cropResistant
|
51694d4d06064f54,7a226222223272dc,0101013131110111,690c8c8ece8e8e4e |
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 487 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.