Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11733A67154CC6F3747A3E3C4A380E66BE2A64144E27BCA4BF9D98B1E12C4A5DCC2764D |
|
CONTENT
ssdeep
|
1536:44ZOPF+O2BTaSPAaiHnQtIXytwyvoipPu2Cgy+:4AOP4HO2a+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
916ab8b1eee994b0 |
|
VISUAL
aHash
|
ff0000006e6e4e4e |
|
VISUAL
dHash
|
71f0ccf0dcdc9cdc |
|
VISUAL
wHash
|
ff0030007e7e4e7e |
|
VISUAL
colorHash
|
02000000030 |
|
VISUAL
cropResistant
|
0001416363490006,d28fcbcb8e8ec694,84c4c0b4a00e1c88,53c08390e0301cc6,5c4ea36064585a31,30c4d0f0dcdc9cdc |
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 174 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)