Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F5829F73704051B302F39AC1E9617E2E72ABF70FC55AC9656EAD41E81FC3DB9BA52060 |
|
CONTENT
ssdeep
|
192:6iVRvVM5aRVFgFKFOVFjMZfDkFFVY7Hgcz+pG6FFVd7HMczPpGHFFVe7HZczepGi:7RM5aRVFgFKFOVFjMwem |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333131cdcccccc |
|
VISUAL
aHash
|
c3c3e7f7e7eff7ff |
|
VISUAL
dHash
|
1e4d040c0c0c140c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07006000000 |
|
VISUAL
cropResistant
|
1e4d040c0c0c140c |
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 27 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)