Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13AC48E71E22852BE044787CDDB627968631EE1EFF1D5C594A65C85A02BE3CE8F90F8D0 |
|
CONTENT
ssdeep
|
12288:WNZiUMo90M37heoHrcwVOBhBxf1Whbv1ifUQjQh4:ho1/HrtV8hBxN20UQjQh4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed6d9292906d4d1b |
|
VISUAL
aHash
|
fff191d3fbffffff |
|
VISUAL
dHash
|
b827323616292222 |
|
VISUAL
wHash
|
1e918181d38f83ff |
|
VISUAL
colorHash
|
07001040080 |
|
VISUAL
cropResistant
|
b827323616292222,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 202 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)