Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B082197612881E3E7213C2E8F7A2F3A8515AD24AD37AC588D1BD53B156D3CD4F927AC0 |
|
CONTENT
ssdeep
|
192:aLghbuuFnYiIIx//kDpGOprDUV5UujwuQUs7ojywAcQSyUZxBcFL/W:UgRJXIw/ktZpwPOo2NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c99ce2e2b6e0b2a6 |
|
VISUAL
aHash
|
ff1818181861e140 |
|
VISUAL
dHash
|
b2b2b2b23283cb88 |
|
VISUAL
wHash
|
ff18181818e1f3ee |
|
VISUAL
colorHash
|
010000001c0 |
|
VISUAL
cropResistant
|
000080a0a0800000,8a8eb2e0a2802b33,a2d1e43a3aecd1a3,5abaaa4bab322eae,1595a86ad4929391,a475d095bd0c6cec,b2b2b2b23283cb98 |
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 87 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.