Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T140A2D96193401A3C551B83D8FBF1F73842AAD3D9E26F8865E3BE06720697C58F9236D0 |
|
CONTENT
ssdeep
|
384:3ALmlLPeLvekbUj3oP3g3Rh3cW3W/3KgP92NjaNcFK:3ALK7erekbYKAhr0z9kaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e45a1b7239cccc39 |
|
VISUAL
aHash
|
0000f8f0e0f00003 |
|
VISUAL
dHash
|
038a40808c86de2b |
|
VISUAL
wHash
|
00e0f8f8f2f707c3 |
|
VISUAL
colorHash
|
39603000000 |
|
VISUAL
cropResistant
|
3230d0599b25b696,455276494b4393ba,22aa16696a535bb2,a0a1c41804a4a4a6,038a40808c86de2b |
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 94 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.