Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B00383B25040753B419BE1C4FA39F769F2C3814ECE194592A3FD87798FCAF91A411A2B |
|
CONTENT
ssdeep
|
384:Q+BvzhDMtDl4P50j7/MPVFnvSd095Rl0Q:Q4LoJ/0ze0fj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1646564679b9a9a |
|
VISUAL
aHash
|
c3c3ffe7c3ffffff |
|
VISUAL
dHash
|
8686b01e9612161a |
|
VISUAL
wHash
|
03434fc3c3c3c3cf |
|
VISUAL
colorHash
|
07c00000003 |
|
VISUAL
cropResistant
|
8686b01e9612161a,07091907871e3ad3,0008046169060000 |
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.