Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T159223326D000681623E38DCCF67ABB3F7356851BCE8A759252E5834F1EC6E96EC65309 |
|
CONTENT
ssdeep
|
192:SaeixapFdDNHYFFmAJgp+7UyS5vPLPhUGHCK:leimN4vmc7UyS5vjP/HF |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8c38c6637b65327c |
|
VISUAL
aHash
|
001e1818197f7f7f |
|
VISUAL
dHash
|
6c3434b333d4f6f6 |
|
VISUAL
wHash
|
001e1818197f7f7f |
|
VISUAL
colorHash
|
0b001000240 |
|
VISUAL
cropResistant
|
e9ecece4e5e5e7e5,db26c93268d3cb99,67676585e4246464,43078767323924c3,6c3434b333d4f6f6,0f3349d8d44d7b17 |
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 5 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.