Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13CB1963611615A2E271385B4F9E1F39881DED34EC9A68958F2BC13AA23C2DD0E873164 |
|
CONTENT
ssdeep
|
48:sEtN/Nc3mkblaraeCgHRCiBJdjX9GrXc/cBw8ZGpbFD/l+Wio8Xn499Y7NSAU9D6:sPJWV1G4kUN+Wi9n4SuSW/vUG3LkCeoG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f131751a4e4e4e66 |
|
VISUAL
aHash
|
00c3c3ffffffffff |
|
VISUAL
dHash
|
8e9e867004100c72 |
|
VISUAL
wHash
|
008100383c3c3c38 |
|
VISUAL
colorHash
|
06000000007 |
|
VISUAL
cropResistant
|
9e9e067004000872,2058a4a468602000,166979294e616112 |
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 71 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.