Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CE03B6B052481BBF524B4AF6F2627FACA1BD974DEA1BD40DB279D2D107CDC48AD122C4 |
|
CONTENT
ssdeep
|
768:5FLYD2SJwoxg3yy39D4NtfEfsm8smYsmgsmss2PYfj/hkWiLQiRD3Q+i:WwqF/vg0 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cb0ab4e897974ab2 |
|
VISUAL
aHash
|
fff9b838f8f8ffff |
|
VISUAL
dHash
|
55937171d313834c |
|
VISUAL
wHash
|
bdf0103070f0f9e7 |
|
VISUAL
colorHash
|
06008030000 |
|
VISUAL
cropResistant
|
55937171d313834c,8633337969797979,4041e5797d79777f |
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 4 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)