Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T120A47231A661293B421B45EDB2B00A1D6283C3508B07A9A1DBF47BB37BC7CA97F5174D |
|
CONTENT
ssdeep
|
6144:2/B+tVw4mvFPejipi3gWFI9VdvlYiDLBP:2zNejQfVdtLDLh |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3bc58c344c743d3 |
|
VISUAL
aHash
|
ff8f2f232f2faf00 |
|
VISUAL
dHash
|
ad595a4b4b4b4931 |
|
VISUAL
wHash
|
fd0f0f232f2d2f00 |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
8d195a4b4b4b4b59,41d4d8c4d4d0d0d0,1616160001000000 |
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 353 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)