Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T191728530C84BE53721A355D0B7726B6FB282A705CE67014B92F8C36D8FD6DE6DC22584 |
|
CONTENT
ssdeep
|
384:GfVDU4IU0EB03/Qbl0imw9QUR9mWyMBuVQ:G9D8U1FbBpuVQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92366d6d6d6d9230 |
|
VISUAL
aHash
|
003c3c3c3c3c003c |
|
VISUAL
dHash
|
e4ececfc786870f0 |
|
VISUAL
wHash
|
043e3e3c3c3e0c7e |
|
VISUAL
colorHash
|
31000000180 |
|
VISUAL
cropResistant
|
8000020b23000080,fff7ffbfdc8cfafb,908080018100c200,c080802d2b8280d0,ffff5f47e737ffff,ff5fc7a7fed155d5,e4ececfc786870f0 |
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 2679 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.