Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D755037AEC0D5A09707675CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:NEfuQXhNSPGEqshNSBGE3hNS5GEr0MJXw:NEfuQP00Gg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311e4e4e0e417b |
|
VISUAL
aHash
|
00c7c3e7f9ff83df |
|
VISUAL
dHash
|
291f9e8f43cb2f2b |
|
VISUAL
wHash
|
00c3c3e3e9fd81cb |
|
VISUAL
colorHash
|
06000018018 |
|
VISUAL
cropResistant
|
291f9e8f43cb2f2b,cac2ccc4a4a4c418,0418597939795804,2d6f676e7676c38f,4d4c4c4d4d96336b |
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 82 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.