Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E2C20C30B486AD374193C2D59BB6571B3AE1E306CB4357099BF8C3AC6BDAD5BEC12148 |
|
CONTENT
ssdeep
|
384:hFAudHgiDM2LynA2AtACAAs0pAluAIGACMFAtxENlPdBH:LVgr7gTASpMuHGTMFwGNlPdBH |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333decccc313131 |
|
VISUAL
aHash
|
ffe7c3c3ffffefe7 |
|
VISUAL
dHash
|
104d1e1e00180c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07400000400 |
|
VISUAL
cropResistant
|
104d1e1e00180c0c,6be3e5ecebeae463 |
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 15816 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.