Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T117231E30A804E93701DB99C85632576A62F68346CA231689FBF5C7F91FEFD28CD67214 |
|
CONTENT
ssdeep
|
768:LAJsIx/jFSSFrd2QdMqE4Uf78Eud4RCG2w:SsIxBSSF1sH78ExR4w |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ad29c49a6cb256cb |
|
VISUAL
aHash
|
ff1b0101000cfff3 |
|
VISUAL
dHash
|
2333231773381e26 |
|
VISUAL
wHash
|
ff9b0101000cfff7 |
|
VISUAL
colorHash
|
07400038000 |
|
VISUAL
cropResistant
|
2333231773381e26,aeaeaecc8ca6ae58,196535d3d3331373,595b5b7051591f1b,7b7b7b7333373218 |
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 129 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.