Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12EC25775760041AB03B799C1E6617E1FB6CAF30F800A8515ABBDE18A2FC3CB6B721575 |
|
CONTENT
ssdeep
|
192:6BVpn30x+FoFgFWFjF4FOOFOFDAMGq9t+cUNJdG0rORFZgFlLkJLQ:0r30x+FoFgFWFjF4FOOFOFDAMa6Q |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333326cccccccc |
|
VISUAL
aHash
|
c3c7efffe7e7e7ff |
|
VISUAL
dHash
|
0e0d0c0c0c0c0c0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000000c00 |
|
VISUAL
cropResistant
|
0e0d0c0c0c0c0c0c |
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 21 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)