Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B0B2F9F0A16547397257C3D44222DA2A32D7B1E8DB0BC28513E487E59AC7DB8CD5E7C2 |
|
CONTENT
ssdeep
|
768:1zYwynSnqmq2ViNxOx5x4CkKCksCk3ZnJlODTNw9uMv:1TkSq1miNMfyWQFn591 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ddfb22220d8c2e2f |
|
VISUAL
aHash
|
c1e8b89888421e1a |
|
VISUAL
dHash
|
1308303030aaaaaa |
|
VISUAL
wHash
|
c1fcf898885e5e1a |
|
VISUAL
colorHash
|
32001c00000 |
|
VISUAL
cropResistant
|
1308303030aaaaaa |
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 150801 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)