Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FFA2B7797584277B098383EDF761AB2EF2D28886D5174565E0FC82169FB7D82CC027A2 |
|
CONTENT
ssdeep
|
384:XzeVrO2c/R+XqL2GjYrJ6HjGYy4o+QCRB3449Bl+3+As:Xze02cJ+XDCjNJ4ic/s |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c0e51d3db01f8fe0 |
|
VISUAL
aHash
|
026074746600007e |
|
VISUAL
dHash
|
a6cccc8c942084a8 |
|
VISUAL
wHash
|
6264767666606c7e |
|
VISUAL
colorHash
|
38000007000 |
|
VISUAL
cropResistant
|
a230c43733cc00a2,a6cccc8c942084a8 |
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 6 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)