Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T127C6B64063D0A858139B5FBA771BB4E6F41F18AF3888485BE250FC6065A972BFEF4531 |
|
CONTENT
ssdeep
|
49152:5sRi6hiYWGXI5bfnjaTU1M99vzChDhJJO10lam9glW7sYNGtbE+6pCL+Hbx3GfFM:WShOT963+1LOvx+e/UmmI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c9e349c2427ef61c |
|
VISUAL
aHash
|
fdfb9b0000ff0000 |
|
VISUAL
dHash
|
59d3369232307211 |
|
VISUAL
wHash
|
fdffeb1800ff0800 |
|
VISUAL
colorHash
|
30003200080 |
|
VISUAL
cropResistant
|
59d3369232307211 |
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 934777 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)