Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EE55047AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:qpf4dQXhNSPGEqshNSBGEChNS5GEBfU0X5:qpf+QPU0J |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f333164b1c1d6b16 |
|
VISUAL
aHash
|
00c7c3e7fff9ffff |
|
VISUAL
dHash
|
190f8f0c2b2b2d0c |
|
VISUAL
wHash
|
00c3c1c78781cfff |
|
VISUAL
colorHash
|
06000000418 |
|
VISUAL
cropResistant
|
190f8f0c2b2b2c0c,c46564646ca85356,0418597939795804,c3d3c3c7c3e3c7cf |
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 55 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.
Pages with identical visual appearance (based on perceptual hash)