Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14E4294C29254A237917342C6FF4A5BA673B6806CE795064242FC82FA1FE8E55EF3315C |
|
CONTENT
ssdeep
|
192:Pwx3roJg+9qheSMW2r4RjUBUY4vFz1c2InU1/sHeQ:PwxcSCr4zhBIny/fQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bb3c1b332727250d |
|
VISUAL
aHash
|
00ffffffffffffff |
|
VISUAL
dHash
|
de31250597dbd979 |
|
VISUAL
wHash
|
008fc7d3e14161ff |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
3939150593cbd979,fffe96d4d4beffff |
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 2 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.