Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F73200A0B097553F267387D572E97F5EA3C1814CCBC6891281EC83BB0B9BE58AC5F460 |
|
CONTENT
ssdeep
|
192:ZrYcEZEAkQgTYCxoF2j6FOjH6OHL5bXySn+nhTnCn+nl9nD/xNuESvVCOpBQ0mjP:aXZi1r52TYG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ecd90cd9590d5917 |
|
VISUAL
aHash
|
18fff7e7e7f10301 |
|
VISUAL
dHash
|
b2834d4d4d252726 |
|
VISUAL
wHash
|
18ffe7e7e7910100 |
|
VISUAL
colorHash
|
076000000c0 |
|
VISUAL
cropResistant
|
b287054d4d252726,103434b494801000,50ccb2b2b2b2b2b2,49c4614155cccc23,c525a72726262727 |
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 11 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.