Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11D832A21E10156382B6B8AF4F05AA65FE3569C0FF76128B1F86E63F35483B64CB7B015 |
|
CONTENT
ssdeep
|
1536:LsYwbgtX8/ShGNMQ6pGVf2kZfddNXP1FEaqq6Iwuuwz3ajisp7en3OwKE+GnIWnA:LFRaqq61uVjajispyn3OXE+GnIWnIji4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b847c7383ec7c0cc |
|
VISUAL
aHash
|
ffcfdd8d8fcfffff |
|
VISUAL
dHash
|
881a39393919060e |
|
VISUAL
wHash
|
7f8988888c8cc3ff |
|
VISUAL
colorHash
|
07c01000000 |
|
VISUAL
cropResistant
|
881a39393919060e,79f547123f6c6703 |
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 1308 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)