Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T192722A7AB21812615E0343EDFA6322EAB2138169DB129BDCC77C421C7395DEDC935DCA |
|
CONTENT
ssdeep
|
192:QoFoB6CJ54t9je8+q3pw4d57Tf/3m6WgHFcRWCUUAoEXI1ku9cuGRmKbMpBXp7ss:QUoCzDpD/ZXOUn/smMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf4ac025d56ad02f |
|
VISUAL
aHash
|
ff818181838381ff |
|
VISUAL
dHash
|
55614d4d46065f48 |
|
VISUAL
wHash
|
ff818183838383ff |
|
VISUAL
colorHash
|
32402018000 |
|
VISUAL
cropResistant
|
55614d4d46065f48,7a222222223272dc,0111013131090001,690c8c8ece8e8e4e |
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 482 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.