Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17462F9B9E21417B18A4347D6FF2132EAE503406E5A527FDCD6688218F19DDEF89218C5 |
|
CONTENT
ssdeep
|
192:QoXoBYJ5J9uHwWx9BAXAyR7fVy9xyRURku9cuGRmKbMpBXp7sfgg8gk:QwogzW3uQy1fV2URUGsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed69929296e0969e |
|
VISUAL
aHash
|
fff991f1fbbffbfe |
|
VISUAL
dHash
|
c81333535363928c |
|
VISUAL
wHash
|
7e8981e18191f3ee |
|
VISUAL
colorHash
|
07000c00018 |
|
VISUAL
cropResistant
|
c81333535363928c,0731297971714d97 |
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 494 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)