Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19922F6F8722414E1EE0397CBB932327AB043917FDEA256D8D3698714B699CFD8850DC6 |
|
CONTENT
ssdeep
|
192:QoYoB6CJ54t9rUHku9cuGRmKbMpBXp7sfgg8gk:QzoC4EsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a92f560ca29a53f |
|
VISUAL
aHash
|
ff7e0918000000ff |
|
VISUAL
dHash
|
dcfc7b713555172e |
|
VISUAL
wHash
|
ffff0919098000ff |
|
VISUAL
colorHash
|
0e610000000 |
|
VISUAL
cropResistant
|
dcfc7b713555172e,be00528c8cd200be,636ac6d6e4bcd97a,8be038fbf9b0b2aa,c4a2ae2212a6a2c4,a292c82b13cc82a2,bcbcbbf1b134d6b6 |
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 485 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.