Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133C2A32872A500550177DEC6E1B56B97ACBDF30EE50A6900DFFE12988FEFA7A7420453 |
|
CONTENT
ssdeep
|
384:w8A7c9jcPMs3BWVBkZ8gkZ8qJqE82382i82Xccms153N:w8AY5cPv3IVBkZ8gkZ8Rccms153N |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a648a3faa9b249b |
|
VISUAL
aHash
|
81f9fbff00003c3d |
|
VISUAL
dHash
|
0121b10911046969 |
|
VISUAL
wHash
|
81ff99ff00003cbd |
|
VISUAL
colorHash
|
38007000000 |
|
VISUAL
cropResistant
|
0121b10911046969 |
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 1330 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)