Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1520320F0644DA0B712A359C4F520BE08E4D2E36AC7E54E8157BDE6E91FC1E987C1B4B8 |
|
CONTENT
ssdeep
|
384:o8zGDNemyj2SFuGcfyUaQiP90cn+29n2KIq82K8C2KG2KQ2KQ2KBhZium2HHiy8:YemAnua+cnX9n2h2vC2h2J2n2OmHx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b131296169cbcbce |
|
VISUAL
aHash
|
c3c3ffe7c3ffffff |
|
VISUAL
dHash
|
1796101e96121e1a |
|
VISUAL
wHash
|
81c3cbc3c3c3c3cb |
|
VISUAL
colorHash
|
07000038000 |
|
VISUAL
cropResistant
|
1796101e96121e1a,eb2ba343d3d39389,7372337353674379 |
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 64 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.