Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19704C77C6001159F6137CAC1B4A1BF0AE0A2F34BCF26E504D6EE1269AFDBC226DE5574 |
|
CONTENT
ssdeep
|
1536:JFhaoHf4jJ8rBKish6WMItgFiElRMpav1t4tBPG1Vp/7tUZL8R+7gU0HBsn+8P/Y:VaoHf4jJ8rBKish6pKgF98gUZL8R+72 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc36339333999c |
|
VISUAL
aHash
|
0018383818180000 |
|
VISUAL
dHash
|
0f35737370734591 |
|
VISUAL
wHash
|
85fc3f3f3c3c1900 |
|
VISUAL
colorHash
|
30200038000 |
|
VISUAL
cropResistant
|
e4e1b0d6d47070c8,0f35737370734591 |
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 66 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)