Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1606396704246461AE697E1C0FE329B4D92958305C3064D6CB7F36927FE8ED74ED3EAA0 |
|
CONTENT
ssdeep
|
1536:x4zcsK4usrGbSntyVAbbUL2odgh6XEiieeekeee8eeeQeeefeeeZeeepeeefeeeR:uJDS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
db95f2e0e3c8c8e0 |
|
VISUAL
aHash
|
ff001808091800fd |
|
VISUAL
dHash
|
793830535ba33919 |
|
VISUAL
wHash
|
ff08183969d880ff |
|
VISUAL
colorHash
|
00038000000 |
|
VISUAL
cropResistant
|
0009696161290078,8080c02b29a08080,3939393939399202,3838305b5ba3b939 |
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 109 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.