Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T170721975F22423B55AC743DAFF2622EAE32240EAD6167F8C9618821CF19C9EFC515DC1 |
|
CONTENT
ssdeep
|
192:QoaoBmJ5/94hH6zQ7M4hLd7DnZejU0SXd/Mu9cuGRmKbMpBXp7sfgg8gk:QtoAET7xDIjUNdUsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
952a55aad5aa55aa |
|
VISUAL
aHash
|
0f01037f7f3f3f7e |
|
VISUAL
dHash
|
3177c7c1c060e1c2 |
|
VISUAL
wHash
|
0001017f3f3f3f3e |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
3177c7c1c060e1c2 |
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 489 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)