Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D3B35CF03658F1A665A347A3A06F2407B37D243F284D4D609354ECED62ACCDAA4A7FC5 |
|
CONTENT
ssdeep
|
1536:eR3kSs6Wytmt6UkCjrpQ4CgD9d2hr7zOUlNtbPTMnPC6T2uAtbzL8J:4NkDShvOsN50Tstbq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9f31716864ce46e6 |
|
VISUAL
aHash
|
00183c3c3c3c3c3c |
|
VISUAL
dHash
|
3872687070716969 |
|
VISUAL
wHash
|
383e3c3c3c3c3c3c |
|
VISUAL
colorHash
|
32002200080 |
|
VISUAL
cropResistant
|
b1e1d4c6a6e95951,ce4de8f4e0e87755,3872687070716969 |
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 63 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.