Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10581D73251661C2D721B828CEA64F77823AFA242DA0F9604D1FD127A57C7DC5EC371B4 |
|
CONTENT
ssdeep
|
96:VuspmMDcOUfjc/9myg1DXeTqVwTCda9462HSYSTSTEOFY:B4OVDsDILh9qyRe4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e0607070723f3e3f |
|
VISUAL
aHash
|
00ffffffffffffff |
|
VISUAL
dHash
|
0990290880400202 |
|
VISUAL
wHash
|
007d1774c0e3d6db |
|
VISUAL
colorHash
|
07000000007 |
|
VISUAL
cropResistant
|
9021000000400210,8000200141010080 |
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 6 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)