Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DF34946072D050EA6257C7C4B071BD62A0A6B39FB826C248E5DDF172EFC7CF46C149A2 |
|
CONTENT
ssdeep
|
1536:cltZkVzN1PLnkXwdU5HJNKDkopwZmfelyu+z3AaUMP2RxvF1lGb8clcVyuReQKLD:c0mw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e520758e73238e73 |
|
VISUAL
aHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
dHash
|
9696969696869696 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07010000180 |
|
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 246 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.