Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EA133F30A080293B0147A6D4AB3A675B73C6D206CB131B15ABF8C79F4FCBD54CD2BA65 |
|
CONTENT
ssdeep
|
768:IeZqdg2z7Yhz4LSzGkXLoMhAs60tN+9fh/od4XsJQO:IeZqxX0tNqZ/DX5O |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8f96f4e88db2a4c2 |
|
VISUAL
aHash
|
ffff3f0939010000 |
|
VISUAL
dHash
|
2261edd3e3d3db66 |
|
VISUAL
wHash
|
ffff3f1b3b010000 |
|
VISUAL
colorHash
|
06c00400000 |
|
VISUAL
cropResistant
|
222365b1ed45d3d3,80c0f0f8f8e86864,1b0f899966cc93d3,8f1b565e8ea5a3eb,e5cc4468e8640859,a1c5d3e363d35956 |
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 22 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)