Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19C931F7CB748AE74082ED7F06E31A0B09D5F249D886577A4C45ACBB2F2724EC69B5C13 |
|
CONTENT
ssdeep
|
768:O2F1rot7a7RRb8uh1k40AcbcwG70FQaYuVhxPVSn97XPAa7DVoh/0wmHjg4NM97a:VrqOjbV2YYPgI/TEXbYm37TCNM/OQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c7963834c7c73c38 |
|
VISUAL
aHash
|
060720707060c0c0 |
|
VISUAL
dHash
|
9c1ec4c9c0c00800 |
|
VISUAL
wHash
|
0f0f1f7c70f0e4e0 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
aa8f4d71314d0faa,9c1ec4c9c0c00800 |
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 28 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.