Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16F23FE31A800DD2701DB9AC95276622A62F68346DA1306C9FFF5C7F91BEBC6DCA33154 |
|
CONTENT
ssdeep
|
1536:FMb0SPtoTvpGHMe+qIMlP2esIxaZw7a0D:FKxW4eMlP2eKw7x |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f261f8f0e2e17268 |
|
VISUAL
aHash
|
ff0000000000ffff |
|
VISUAL
dHash
|
04364b49ad9c20a4 |
|
VISUAL
wHash
|
ff82000000cfffff |
|
VISUAL
colorHash
|
1b0000001c0 |
|
VISUAL
cropResistant
|
8800004c000f0c32,8c00b047272684ac,000000c088004040,361b4b490dadad9c |
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 56 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.