Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F6349460B2D051AA6257C7C4F071BCA2A0A6B39FB426C24CE5DDB161EFC7CF46C549E2 |
|
CONTENT
ssdeep
|
1536:CNtZkVzN1PLnkXwdU5HJNKDkopwZmfelyu+z3AaUMP2RxvF1lGb8clcVDnRSQKLG:CM0d |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e520718e7323ce73 |
|
VISUAL
aHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
dHash
|
9696969696869696 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
070000400c8 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a0a0a0a1a2a2,44d0aa2aa38cb233 |
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.