Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A7038E347182386B2C7B6AC5F0946F1A70C3E7B6C2590ECCA7E683542FDACE09765365 |
|
CONTENT
ssdeep
|
384:8r1eXI7UewD5xMDpmU0KVMgonpGtTzhBeC3L:6eXI7dwD5KDpmU02H9tTzhBeC3L |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
da2d0d5a85d3a5d2 |
|
VISUAL
aHash
|
0000fffffcfcfcff |
|
VISUAL
dHash
|
7071006969696949 |
|
VISUAL
wHash
|
0000bdfcfc7c38fc |
|
VISUAL
colorHash
|
06001008180 |
|
VISUAL
cropResistant
|
7071006969696949,f0f0f0f0727533b5 |
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 43 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.