Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BA72186FB2141AB08D0243C6FD1213FFD621903DB95156E8E7E98728B2999ED8831FC9 |
|
CONTENT
ssdeep
|
384:QMoCfjkLu3I76B4ARtzxdiEGkYd4uAsmMpBZ7eg/B:RokjZu6O6tMEke0m4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f5aad5aa55aad408 |
|
VISUAL
aHash
|
efc381e701e7e7e6 |
|
VISUAL
dHash
|
0c8f238c1f0e4d0e |
|
VISUAL
wHash
|
ef0181c700e7e7e6 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
0c8f238c1f0e4d0e |
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 490 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.