Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11D1284262094A03B569307CF7E604B1E71EA62BCC7334D59F6F843E59785C5B9E2908A |
|
CONTENT
ssdeep
|
96:TG+rskTfd4/4hqfU+EtwML+NgKX3q4MUZjT4AZhrlrm55wsc5l5H5quPn5poRkjx:CqrduMLQgK1lm55wn5P5B5pnDpOiX |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e45b2c0e1b6e4b2d |
|
VISUAL
aHash
|
0002c8dcfff7d7ff |
|
VISUAL
dHash
|
73acaa39daa6a606 |
|
VISUAL
wHash
|
00044088fff7d3ff |
|
VISUAL
colorHash
|
02200038000 |
|
VISUAL
cropResistant
|
d24042626a6242d2,acaa39b148a6a606,8c6163738d629190,6f2bcf6733991131,23f3e7e5a62c2931,a429181b3823c2e1 |
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 46 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.