Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16F83C6F0131A2779731F05A4B470A7E83566B3AAD927CC08D3FE115A17FEFC18A19A91 |
|
CONTENT
ssdeep
|
1536:jQpNL07xplGjSfp5cuAC2skCX43VIRyYwWaFZ6Ep4tWbkcKi:jQbg9pz3cuACYL22WeZb |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e674dd9a93996122 |
|
VISUAL
aHash
|
9c80c3e7e7ffcbc3 |
|
VISUAL
dHash
|
212796cdcd132b2b |
|
VISUAL
wHash
|
8000c0e7e7ffcbc3 |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
212796cdcd132b2b |
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 290 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.
Pages with identical visual appearance (based on perceptual hash)