Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AC630014724106FB1667DAE0E060FF5961EFF34AC66BC98966AC20622FCFCF879515B0 |
|
CONTENT
ssdeep
|
768:4JZ5b1b55bNbNb4bBYdd5Okh7yzUwi9HN9NrNON0+NxNdMNFNKr08cpCwTHyMcEG:25Z15xhMl+5O67dHvCwIq27 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
842a3b3acbeaaa3a |
|
VISUAL
aHash
|
0102067636160662 |
|
VISUAL
dHash
|
931c94c4e4e40cc2 |
|
VISUAL
wHash
|
4106067e7e7e067e |
|
VISUAL
colorHash
|
38042001000 |
|
VISUAL
cropResistant
|
931c94c4e4e40cc2 |
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 57 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)