Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1114385F25480663702D753D5AB78B71AF2D2D197DD0626138EF08B6E4BCBE91EC12872 |
|
CONTENT
ssdeep
|
768:56ipuYa0O2Z4EAvEASa2sfo5VZbVnQJgl:N5Z4EAvEASaKdQel |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1134c16795f315b |
|
VISUAL
aHash
|
00ffcfc7c7c7f7c3 |
|
VISUAL
dHash
|
f00e1e9e9f1e0f07 |
|
VISUAL
wHash
|
00ffc7c3c3c7c381 |
|
VISUAL
colorHash
|
0f002000041 |
|
VISUAL
cropResistant
|
2e9e9e9f9e1e0707,10d0d8f003f0e408,ccd690b29273f08d,1423d4d4d4331410,0000810045011411 |
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 5050 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.