Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16562981460619A7FA5E38AE4F6E1736019BED309D2B2415AF0FC03F617DECA5D633A90 |
|
CONTENT
ssdeep
|
192:ag8YOGqoOe4SDcdqGOqkqOa1KB9TeB69h7Ez6GEcScAD4nne6dBOe5v:R8nBoGLpOeKXes67gi |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d94c4c4c4ce6e6e6 |
|
VISUAL
aHash
|
0000ffffffffffff |
|
VISUAL
dHash
|
32320c1030181010 |
|
VISUAL
wHash
|
0000000cdfcfdfdf |
|
VISUAL
colorHash
|
06000000038 |
|
VISUAL
cropResistant
|
a2b2d0b2b2e8a082,300c103018103010,606432b232b22432 |
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 18 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)