Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F954976C301215AF61B3CAD0B4A1BF0BB0D1F30BDE6DE60595EE12156FCBD22A9E1674 |
|
CONTENT
ssdeep
|
1536:LsLGLoHf4jJ8rBKish6WMItgwQ2E4iKQVjQvBFaDy6cav1t4tBaR1Vp/7FUZL8Rw:yGLoHf4jJ8rBKish6pKgwQ1hUZL8Rn7k |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc36339333999c |
|
VISUAL
aHash
|
0018383838180000 |
|
VISUAL
dHash
|
0fb5737370724451 |
|
VISUAL
wHash
|
85f83f3f3c3c3c00 |
|
VISUAL
colorHash
|
30200038000 |
|
VISUAL
cropResistant
|
e0e1b0d4d47170c8,0fb5737370724451 |
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 33 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.