Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FA835DF56580FD1342B340D2709F8A47B3BE491BBC0A4C90B69CC6C673FA8B615676E6 |
|
CONTENT
ssdeep
|
1536:klLRgbHKcpVd3brjmjefzTNph5EEA+pifzTNph5E45o0cCmeeR0ezL//J1tl4iRX:kGE4MVw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3396d96346d3896 |
|
VISUAL
aHash
|
002008007e7c7c7e |
|
VISUAL
dHash
|
9cc8e9d4eccce0c4 |
|
VISUAL
wHash
|
003c0c007e7e7eff |
|
VISUAL
colorHash
|
38200008002 |
|
VISUAL
cropResistant
|
e80c56862baba3c2,1632607866f8f0b4,f696b3a3b672b49c,ecdcdedc4ccccef8,949619373f3c4bcb,9cc8e9d4eccce0c4 |
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 37 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)