Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E7F21F66C1629EBB0523D1C1EEA0AF2BF3810189CA670E4573F99B2B9BDFD40DC41647 |
|
CONTENT
ssdeep
|
768:dzY6uP2xm4oQURPbRkTUjaRRPhLFKNIIIIIo7e+FB+9k9YrCVsfmJZ2DwN63kxOr:dzY6uP2sZQURPbCTUjaRRPhLF4IIII7M |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce9ecb6163666161 |
|
VISUAL
aHash
|
3c3c3c3600000000 |
|
VISUAL
dHash
|
6971706d9a969696 |
|
VISUAL
wHash
|
3c3cbfb7c1c1c1c0 |
|
VISUAL
colorHash
|
00000000e00 |
|
VISUAL
cropResistant
|
691091f3556d64ab,6971706d9a969696 |
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 40 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)