Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19A632E24B20146FF5AA7C9E0F061BF1962DAF34AC77BD959A7AC10A12FCECB075111B1 |
|
CONTENT
ssdeep
|
768:DSt5b1b55bNbNb4bBYdd5Ozhkz7KVRrkF/h/oA/1R/3Qb/9I/pC/0/45rc8xSCwW:K5Z15xhMl+5OdkzNVCwzq2M |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
842a3b3acbeaaa3a |
|
VISUAL
aHash
|
0102067636160662 |
|
VISUAL
dHash
|
131c94c4e4e40cc2 |
|
VISUAL
wHash
|
c106067e7e3e067e |
|
VISUAL
colorHash
|
38042001000 |
|
VISUAL
cropResistant
|
131c94c4e4e40cc2 |
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)