Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11341A775502085CF0313ADEEF4D1B65AE46FE21EC6B3A880B1A4015A2BE4D21C8355A7 |
|
CONTENT
ssdeep
|
48:Jh+1bOVwmQGr38KO4tTRO/vRVftILElj7yjfqPlLfTN4EH:JhOKwmRbO4tTR0vRBtILEpaMfTjH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b62686c9cdcd8939 |
|
VISUAL
aHash
|
e7c7c7e7ffe7ffff |
|
VISUAL
dHash
|
0c0c0c0c080c0000 |
|
VISUAL
wHash
|
03030303e4e4fcfc |
|
VISUAL
colorHash
|
07007000080 |
|
VISUAL
cropResistant
|
0c0c0c0c080c0000 |
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 170 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.