Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T111B33EB03215747B25B387A330EA6612B26D961FDC0F4C90B358F897239CCDAB457B99 |
|
CONTENT
ssdeep
|
1536:f/DMXwvb9WzQo2h20VTj/oDtVPTMnEWPvGurxhdfKI:4Xx0MujgDnavnxhT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1394e4637464779 |
|
VISUAL
aHash
|
00cbcbcfcfffffff |
|
VISUAL
dHash
|
bc9b9b9a9a98d2d2 |
|
VISUAL
wHash
|
00404143c1cffffe |
|
VISUAL
colorHash
|
07000000c40 |
|
VISUAL
cropResistant
|
989b9a9a9ad0d2f2,091496949c969409,bf7ffffffffffffe,973b713bbb3f3f3f |
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 32 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.