Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F8E28331A019A93F0697B7D1EBB5A36AB396838DC947472A82FCC75C4FEBC50DD06490 |
|
CONTENT
ssdeep
|
384:SqIItkSLQhIIIII9ElBHKzhP21m+UEJLDM0sMXC1l+y/O8knpGpW:DIItkZhIIIII1Ju9UwnCMXqlP/RknpB |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
87e3711c9c396396 |
|
VISUAL
aHash
|
00e3e7ff7f181810 |
|
VISUAL
dHash
|
97c7cbf3e5f3f0f0 |
|
VISUAL
wHash
|
00e3ffdf7f181810 |
|
VISUAL
colorHash
|
19030000000 |
|
VISUAL
cropResistant
|
f3e3d3ca9d888c8c,0000706969000000,97c7cbf3e5f3f0f0 |
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)