Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1363450B1A24119BAC7174AD9B0D9630D676BF64DCFC61085DFB903F42BEBCA8E40D129 |
|
CONTENT
ssdeep
|
1536:FnhUE4APdRylAGo7Y6Lke5zJjCFrYa00YOszRDQHbeIHAxO5/GylduLm95lm4XqF:Fnr4ou7S |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8f5aaa086c6b78ad |
|
VISUAL
aHash
|
013f8c0032003fff |
|
VISUAL
dHash
|
61693946e6494547 |
|
VISUAL
wHash
|
01bf8d203e003fff |
|
VISUAL
colorHash
|
39201408000 |
|
VISUAL
cropResistant
|
c0e2a6b6d4b0f3e5,efefa36f464e2d9e,8c9c2632b2939a3e,a08080a5a580a0a4,9f878393938f8f84,f8fcfcfaab3325e5,f6f6f6ffedf6f6f6,61693946e6494547 |
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 280 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.