Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11EA3DC238159752B4437C7C1306A5B3BE1A6D99FFAEB0A011EDCC7F72AF9CA0741A119 |
|
CONTENT
ssdeep
|
1536:k78khZH+Y2NsjjntzxptNxLT99nZ8ZIR5x5P5OZrtKxOZUZc5eNNxrNAVGZ4QZdF:eUM8Bb9YwnG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
926d6c13136c6d6d |
|
VISUAL
aHash
|
001f013f7e0f0503 |
|
VISUAL
dHash
|
d9fc27dcdcdcbde7 |
|
VISUAL
wHash
|
000f033f7f0f1f17 |
|
VISUAL
colorHash
|
00003400400 |
|
VISUAL
cropResistant
|
f96ffdb8b8796bcf,d9fc27dcdcdcbde7,536bcc6b63cc5555,1e6701130e1c3424,94210c3232040921 |
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 113 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)