Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16024F950235051E8A14387E4B1706D2B61BFB29AB9B7C14CAEDD15A1FEDBCF8D824C93 |
|
CONTENT
ssdeep
|
1536:qQltZkVzN1PLnkXwdU5HJNKDkopwZmfelyu+z3AaUMP2RxvF1lGb8clcVxd2utWg:H0wwusRE/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1269b8e61796c71 |
|
VISUAL
aHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
dHash
|
8e8e969696969e9e |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
17200030000 |
|
VISUAL
cropResistant
|
0202020202020202,8080808080818282,126266e48666661a,9a9da6aa2ba28cb9 |
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 535 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.