Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A83234A03140567B226784F1F2217F96E0E5BB1BD52FC431A5FC42A61FCFDA0EA10E95 |
|
CONTENT
ssdeep
|
192:q5EbDCdIzmKtYMQAeA7Tp4XypdmjU9RdMpWak:gMXepordM0 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
931717071d26eee8 |
|
VISUAL
aHash
|
000cffe7ffe7ffff |
|
VISUAL
dHash
|
f0d80d1c184c6c39 |
|
VISUAL
wHash
|
004c3400ece4f4dc |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
f0d80d1c184c6c39,0001010b0b010100 |
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 5 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)