Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C0A3DC234259362B4437C2D034BA5B3BD2A6D99FFAE609401EDCC7FA2BF9C90741A51D |
|
CONTENT
ssdeep
|
768:/KjwuitpR4nXF6YjOpSpFlTC6rrWoPQkH0q7r/0E:/KjOtpR4nXBKpSpFl26vTPQkUAr0E |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92136d29d3136d2f |
|
VISUAL
aHash
|
00030e3e2e0f01ff |
|
VISUAL
dHash
|
dcb77cfcdcb97700 |
|
VISUAL
wHash
|
00070f3f3f0f01ff |
|
VISUAL
colorHash
|
00003400400 |
|
VISUAL
cropResistant
|
bd777cfcdcbb7700,dcbf7cfcdc9cb377,d5534bc51e5b5a8d,4c8f9141434e4a5a,ec114c3232080041 |
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 115 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)