Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A1B49EB1B61C50BE00574BCAD7617E4C232EE26BF69588906A6C45B01FF3CA5FE5F4A0 |
|
CONTENT
ssdeep
|
12288:7DMBkmQ90M37heoHrcwVOBhBxf1Whbv1ifUQjQDm:GQ1/HrtV8hBxN20UQjQDm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed6d9292936d4919 |
|
VISUAL
aHash
|
fff191d3fbffffff |
|
VISUAL
dHash
|
9827321656292602 |
|
VISUAL
wHash
|
7c918183a3c383ff |
|
VISUAL
colorHash
|
07001040080 |
|
VISUAL
cropResistant
|
9827321656292602,e03233250d69271f |
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 118 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)