Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T111A195309088573703A343C2EB6A672F67C1C6868D0B5B15CDFA436C5ACDD8AEDA2795 |
|
CONTENT
ssdeep
|
96:3f4NdHEK/F1ysYvhiqy8NCtNpWoNLHjdTm+9V:PUHhpYvYqy8NCQolxmQV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3e64c994c9b3346 |
|
VISUAL
aHash
|
00ffe7ffffffef00 |
|
VISUAL
dHash
|
0c0c0c0c0c9c9c32 |
|
VISUAL
wHash
|
00e7e7ffe7cf0000 |
|
VISUAL
colorHash
|
06008000c00 |
|
VISUAL
cropResistant
|
4d0c4d0c140c9c1c,00200c7030300c20,00100cb2b2303210 |
Fake Serasa Limpa Nome site positioned to capture victims through SEO tactics, typosquatting, or paid advertising. Serves as entry point for multi-stage attacks including credential theft and malware distribution.
Malicious code is obfuscated using 2 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)