Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FFB1BF309414703E11079A9CFA6253DBB2FFD197FA76182496BDE7B24B93D98D807E01 |
|
CONTENT
ssdeep
|
96:T0J0Lb75AKZjxCn52E+/hL8Rj2yHqaq50ymtSW94:xbBZ1r8qOvy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
aa8275ff12d06f60 |
|
VISUAL
aHash
|
00ffffffffffc000 |
|
VISUAL
dHash
|
06c161b975512113 |
|
VISUAL
wHash
|
00f97f3f9d9dc000 |
|
VISUAL
colorHash
|
08000000380 |
|
VISUAL
cropResistant
|
3ff8c21010c2f83f,06611804024100fc,c4c2d188a4a20100,06c161b975512113 |
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 32 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.