Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17F32633971A5533B42FF17CAB1A1B364B092911FFE0754E092BD93F807DAEC5798280A |
|
CONTENT
ssdeep
|
192:+ArhkcKciSytvM9zy2Uy4hK3cDjB48xWqZthpnmuns1GpROsF:+wkcK8ytvg2Ty4UsDjB48xzVRs1GpR9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3896562d926cc63 |
|
VISUAL
aHash
|
f9e7e7e7efe7e7e6 |
|
VISUAL
dHash
|
2b0c0d0e4a4d4d4e |
|
VISUAL
wHash
|
81c38702e7e7e7c2 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
2b0c0d0e4a4d4d4e,1d808080a0004202 |
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 16 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.