Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19D133BF2526471A0C21BCFF6E4B2BA3632E710FCAB5F885096F957645295BECDF48081 |
|
CONTENT
ssdeep
|
768:Nx8wgoghHNt1/3185EP9keFbSHN5iPGdLt4adHxT+Q+sSVVKEHPkqXZW7Glmeem+:Nx8wgoghHNt1/3185EP9keFbSHN5iPGD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed6d92926c64929b |
|
VISUAL
aHash
|
ffc3d3d3d3ffe7ff |
|
VISUAL
dHash
|
a816161616090c10 |
|
VISUAL
wHash
|
7040d0c0d3e7e3f3 |
|
VISUAL
colorHash
|
07007000400 |
|
VISUAL
cropResistant
|
a816161616090c10 |
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 21032 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)