Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FC6319BAB2642676516347C3AC20575932F760BEEE374610D3FC4BE5E7FACE8A409844 |
|
CONTENT
ssdeep
|
1536:9maxjN9ZzGHz35eeeNeI59ULvotdwKAVmax4bU:RAIw7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b8c962cdcc6dc329 |
|
VISUAL
aHash
|
fbdfcfdfdbff8185 |
|
VISUAL
dHash
|
233c3c3632320f2d |
|
VISUAL
wHash
|
f98f878381ff8084 |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
233c3c3632320f2d,e2f09060a898b0a0,36b3993335aca964,de21a6b6a6c6b6a6 |
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 1110 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.
| ID | Português | Inglês | Trigger |
|---|---|---|---|