Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C5144B70A179353E579F24C8F325674A3283E30FE68603F472659AA027D3DE9AC4B754 |
|
CONTENT
ssdeep
|
3072:7lXMT/qwyNwarwaAYQ5X9WkK0ybI8Z1n820D0j/cr:7aKhfQ5X9WL1uD04r |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e28f5c15b66a1b98 |
|
VISUAL
aHash
|
fffff1f1ff00c0c0 |
|
VISUAL
dHash
|
44a6cb458c8cb6b4 |
|
VISUAL
wHash
|
fffbf1e1f7000080 |
|
VISUAL
colorHash
|
0f400000c00 |
|
VISUAL
cropResistant
|
44e6e3eb470d8c8c,b7f2c0f2e6c0ded6,26262a22338c0d3d,888ccc8cb6b6b6b4 |
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 81 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)