Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EC522C75E22412E19A4243C6FE3126E9E113517EAAB25BDCC7188248B3D9DFFC825DC6 |
|
CONTENT
ssdeep
|
192:QonoBS5l4bYTSX/rHDXkr/PxCDeku9cuGRmKbMpBXp7sfgg8gk:QkockYTSrM/PqhsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
95aa55aa55aa55aa |
|
VISUAL
aHash
|
1f033f3f3f1f3f3e |
|
VISUAL
dHash
|
61ce6cc0e0705962 |
|
VISUAL
wHash
|
00030f3f3f1f0f3e |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
61ce6cc0e0705962 |
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 484 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)