Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14755037AE80D5A0A707775CDE3DC0D8FE995F357E32218E696C5DF31818A814B82A87C |
|
CONTENT
ssdeep
|
1536:xTTQHf9gqQUGAQXhNC8eqkfWKwPFwqGutEqshNC8eqkfWKwFPw+cutEQiJnP6RrW:hefr5QXhNSPGEqshNSBGEchNS5GErnX5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eb3412cb96166b36 |
|
VISUAL
aHash
|
000000fffff9ffff |
|
VISUAL
dHash
|
291786042b2b2f0c |
|
VISUAL
wHash
|
00000081fff9ffff |
|
VISUAL
colorHash
|
060030000c0 |
|
VISUAL
cropResistant
|
46282b2b2b2c0d0c,68291d1e87870686 |
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)