Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F545F57AEC0C6A09707A75CDE3DC0D8FE955F357E32218E696C5CF31918A818782A97C |
|
CONTENT
ssdeep
|
1536:dpoJfBa8chNFteqTMW6wlD6xHWt0q7hNFteqTMW6wL96NVWt0FiJnP6RrAF0/Vt7:wfw8chNQDu0q7hNQlu0QhNQ5u0riX+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e333164b5b16724b |
|
VISUAL
aHash
|
00e3c3e3f9fdffff |
|
VISUAL
dHash
|
39078f8f634ba4d0 |
|
VISUAL
wHash
|
0000c1c1b9b9ffff |
|
VISUAL
colorHash
|
06000010018 |
|
VISUAL
cropResistant
|
190f8f9f634ba4d0,0418597939795804 |
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 79 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)