Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T106035FB01660E63B13E3C6C4A7356B9A77C2828DDAB3124A43F9C74D8FDBE95CD16241 |
|
CONTENT
ssdeep
|
768:n0j7N6UVfXt5vA3Zuk77+iHbJpi/T5vsIyVtA61Wq9cU:0V6UVfXt5AZukn972T50Iyf8xU |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c33c6d92922d6de1 |
|
VISUAL
aHash
|
0070600c6c646060 |
|
VISUAL
dHash
|
26c0c0c9cdccc2d0 |
|
VISUAL
wHash
|
a270607c7c7c787c |
|
VISUAL
colorHash
|
38000200030 |
|
VISUAL
cropResistant
|
26c0c0c9cdccc2d0 |
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 101173 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)