Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13B923B7AB31831744B4343D7BA3323FAF267C0BD9752169CE259820C72868ED85B6EC5 |
|
CONTENT
ssdeep
|
384:QzoCOqQGsKO+55ge62LVKlNAksMsmMpBZ7eg/B:cosxsKO+WCVGNAJm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a55aad588 |
|
VISUAL
aHash
|
0081ffe7efe7e7e6 |
|
VISUAL
dHash
|
0909094c0b0d4d0e |
|
VISUAL
wHash
|
0001ffe781e7c3e6 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
0909094c0b0d4d0e |
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 485 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.