Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18D43A5602680987F619383E4D3B5BBAE32C6A256DE170945D3F5436D8BC9DBCCD27A80 |
|
CONTENT
ssdeep
|
384:dBRmzFm7Tk1z67E8QH1tDQHBNlQclKbYRYyH7fLHD37NKtB9D7RNMRQH/qGmV3FB:dm4WViHHWclpjzDrNKxI15SbQhcUgDrE |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b54b5ab42db5d04a |
|
VISUAL
aHash
|
8000720307460602 |
|
VISUAL
dHash
|
1b418686869c6c04 |
|
VISUAL
wHash
|
cf007f7777460606 |
|
VISUAL
colorHash
|
07000030000 |
|
VISUAL
cropResistant
|
7a765a62d99cfcd1,1b418686869c6c04 |
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 309513 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.