Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T104A34B71385DA33B157742C7B0DA2507F3B7A14F94494C50B308EEE93AB8CA6606BF96 |
|
CONTENT
ssdeep
|
1536:OWVyNyjtx0oGff8jMBRf7YPT4ZxSCke5PbJ5eI0Nx+nlvXz74YwNBIZFrcoBb338:XHOR74E9/lkT/j2Ir0xy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9b9b6c649b32326c |
|
VISUAL
aHash
|
003c1c3c38001018 |
|
VISUAL
dHash
|
4df0e8f8f0c4f0e8 |
|
VISUAL
wHash
|
807e7e7e7e001c3c |
|
VISUAL
colorHash
|
384000001c0 |
|
VISUAL
cropResistant
|
9b9a9eec1932e498,4df0e8f8f0c4f0e8 |
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 1553 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.