Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A055047AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:oSfSdQXhNSPGEqshNSBGEuhNS5GEb5ErX5:oSfgQPP6J |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f331134b1e166b35 |
|
VISUAL
aHash
|
00c7c3e7fff9ffff |
|
VISUAL
dHash
|
391f9e0e2b2b2d0c |
|
VISUAL
wHash
|
00c3c1e38781cfff |
|
VISUAL
colorHash
|
06000000418 |
|
VISUAL
cropResistant
|
191f9e0e2b2b2c0c,a2ae94a8d874b4a4,0418597939795804,d3d3c7e7e6e2cbcb,783c2f27343a1e9e |
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 54 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)