Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T176E2A331A048683F069B73E1FB75A35B6295838DEA434B2582FD878C4BEBC90DD075D9 |
|
CONTENT
ssdeep
|
384:wdII2k/8IIIII9IlBMHcs9bUgiHelBUpb8c8oYEfasWfECF5SVX9ea4HQ8pW:QIIGIIIII6sFUgiHenUpQPEfTWfExAap |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3e37c1c3961c69c |
|
VISUAL
aHash
|
00e3f7ef3f3c1818 |
|
VISUAL
dHash
|
87cfcdcbf1e4f0f0 |
|
VISUAL
wHash
|
00e3f7ef1f3c1818 |
|
VISUAL
colorHash
|
19030000000 |
|
VISUAL
cropResistant
|
f3e3d3ca8d988c0c,0000c8c4c4c00000,87cfcdcbf1e4f0f0 |
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)