Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14D1356B212875A2F8A93C0C6F7756B49E2C5935BC2210D45B7FA870F9FC2D24FC1A265 |
|
CONTENT
ssdeep
|
768:hYNrzGNt9Zs+GPTnBbbQNKhrp+ohCyoxaSrE0X1Xmh2fld1ClthJDF/fi0n+ml2a:c0QewfGwvasF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c72d9e9039936cc6 |
|
VISUAL
aHash
|
00203060007c7e90 |
|
VISUAL
dHash
|
dcc4e2c682c4d455 |
|
VISUAL
wHash
|
0670f062607cfebd |
|
VISUAL
colorHash
|
30001010200 |
|
VISUAL
cropResistant
|
80809796614b8880,84809696e18d8ca0,02002632690e0c00,dcc4e2c682c4d455 |
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 154 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.