Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B9E13531A405582B566395D4FBA2FFCD2292D34DCE0A1650ABAC01DA1FD3EF1E4672B3 |
|
CONTENT
ssdeep
|
96:6r8H0Mx7dgudROHkQwIOf/SYeh2xkve7KOyt2ZziiyiQKpEkgwhSB8pLLBQQrG9V:6QNRo8fuve7KOyt2ZziriQL4Lw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b636668c93339933 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d4d4d4d4d4d |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000038000 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a0a0a0a0a0a0,00100c3232000000,85c4230592b24182 |
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 449 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.