Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CB55157AEC0C5A09707675CDE3DC0D8FE995F357E72218E696C5CF31818A818B82A97C |
|
CONTENT
ssdeep
|
3072:lfo8chNQDu0q7hNQlu0ghNQ5u0Lil7uX6:lfo8G+il7uK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e3311e5b193e116e |
|
VISUAL
aHash
|
00e3c3e7f9ff81ff |
|
VISUAL
dHash
|
390f8e9f435b2f2b |
|
VISUAL
wHash
|
00c3c3c3e1fd81df |
|
VISUAL
colorHash
|
06000600018 |
|
VISUAL
cropResistant
|
190f8e9f435b2f2b,0418597939795804,9c9e998dad8b9a96 |
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 80 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.