Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CBF2EAE280A67C3E415B81E9ABA05F6E73E0A145D96E0394D6E4C33F1AD1CC1FC36D54 |
|
CONTENT
ssdeep
|
768:nEgA66aECYqJ6HU4JV1oZO1urJjzG5EWL4dyqHUsDgquSt3lV:5ijL4RHAe3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9332ed0992e69e99 |
|
VISUAL
aHash
|
ff0004040c0800ff |
|
VISUAL
dHash
|
4c086ccc98188730 |
|
VISUAL
wHash
|
ff080e7e0e0e00ff |
|
VISUAL
colorHash
|
3a000e00000 |
|
VISUAL
cropResistant
|
0040004c4c500800,449c951c94109004,bc7cfcbcbcbc04fc,0001000240a05631,191a6ccc98580806 |
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 317 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)