Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T160C30B70A140293F125F47A97160FFE9E19EE349CA6FE958F3BC425223DFCA18E22554 |
|
CONTENT
ssdeep
|
3072:cMAQ+i12ByPJtEGM0/LiLNTnHFhJRMpI/J9iZXSDP8u:cMAQ+igBCJtEGM0/LiLQIx9isDP8u |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e4ca9bb5c4c0e1ba |
|
VISUAL
aHash
|
ff0060f646060000 |
|
VISUAL
dHash
|
9831cecc8cd6d601 |
|
VISUAL
wHash
|
ff80f0f7e7660000 |
|
VISUAL
colorHash
|
30038000000 |
|
VISUAL
cropResistant
|
005012d8d8825000,0411ceccccd68601 |
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 89 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.