Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10EE2E6319048683F069BB3E1FBB5A31B62958389EA43471982FD87491FEBC90DD075E9 |
|
CONTENT
ssdeep
|
384:wYII2kL8IIIII99lBMHE89bUsiHelB4pz8c8YY4jCsWLMGdhSRXcea4HQ8pW:pIImIIIIIX8FUsiHen4pI34jLWLMFfap |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c7e35c1c39639619 |
|
VISUAL
aHash
|
00e1f7e77f3e3818 |
|
VISUAL
dHash
|
87c7cdcbd9e5e2f0 |
|
VISUAL
wHash
|
00e1f7e77f3c1818 |
|
VISUAL
colorHash
|
31030000000 |
|
VISUAL
cropResistant
|
f3e3d3cacd988c8c,0000c8d4c4000000,87c7cdcbd9e5e2f0 |
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)