Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133622B75722426B49E0343CEFA6663BFF31351ADEA5206C8E7958318B1859ED8C34DC5 |
|
CONTENT
ssdeep
|
192:QoOoBOJ5794LgI793kl5NuRuas3tjku9cuGRmKbMpBXp7sfgg8gk:Q9oUp8NkMRPQQsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a552a55aa |
|
VISUAL
aHash
|
00c3e3e7fffffffe |
|
VISUAL
dHash
|
510f4d0d334d4d2a |
|
VISUAL
wHash
|
808100e7ff01f7fe |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
510f4d0d334d4d2a |
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 491 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)