Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T192829A35760141A703F79AC1F661BF1EB2D6E30FC40A8525AABD918A1FC3CB57B71262 |
|
CONTENT
ssdeep
|
192:6iVRXYmhVKRF9FFF8FCFyFODMlr9tRuxK89HFpLwX:3PhVKRF9FFF8FCFyFODM2o |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33333338ccccccc |
|
VISUAL
aHash
|
c3c3ffffffe7ffff |
|
VISUAL
dHash
|
0e4e060c0c0c0c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07008008c00 |
|
VISUAL
cropResistant
|
0e4e060c0c0c0c0c,0000080188aa80a2,ac2c4cecc80aaaa2 |
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 23 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)