Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19CD273B351869D3F02A7D2C4A720BB69E1C3520ECBC55100F6E9174B6EA3DE1FC259E9 |
|
CONTENT
ssdeep
|
192:WpZ/o5gaLprBRb4GCdYtZglVMrbDIgV0NeeO5TVjzwI3QLipDIxV0N:WigaNBoOtGgDII0FwXnALMDIP0N |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b347cc3067c63273 |
|
VISUAL
aHash
|
e6cfe7f18387ffff |
|
VISUAL
dHash
|
0e3b4c6b0f1c421e |
|
VISUAL
wHash
|
8683e7a1878787c7 |
|
VISUAL
colorHash
|
07002200600 |
|
VISUAL
cropResistant
|
0e3b4c6b0f1c421e,b058d9c9c3d65c2d |
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 33 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)