Rmissax Full

Performs discovery and vulnerability checks.

# Basic TCP port scan of a CIDR block + banner grab
rmissax scan -t 192.168.1.0/24 -p 1-65535 --plugins portscan,banner
# Full recon: DNS enumeration, SSL cert inspection, CVE lookup
rmissax scan -t example.com \
    --plugins subfinder,crtsh,sslinfo,cve-search \
    --output results.json --format json

| Option | Example | Meaning | |--------|---------|---------| | -t, --targets | -t 10.10.10.0/24,10.10.20.5 | Target IPs or hostnames (comma‑separated). | | -p, --ports | -p 80,443,8080-8090 | Port list/range for the portscan plugin. | | --plugins | --plugins portscan,ssh-brute | Comma‑separated list of plugin identifiers. | | --exclude | --exclude 10.10.10.5 | Omit specific hosts from the scan. | rmissax full

# Assuming rmissax is installed and loaded
library(rmissax)
# Sample dataset
data <- data.frame(
  id = 1:10,
  numeric_var = c(1, 2, NA, 4, 5, NA, 7, 8, 9, 10),
  categorical_var = c("A", NA, "C", "D", "E", "F", NA, "H", "I", "J")
)
# Smart imputation
imputed_data <- smart_impute(data)
# View imputed data
print(imputed_data)
# Visual assessment
hist(data$numeric_var, main = "Before Imputation")
hist(imputed_data$numeric_var, main = "After Imputation")

| Aspect | Details | |--------|----------| | Purpose | Comprehensive missing‑data analysis & imputation (Exploratory, Diagnostic, eXtra‑impute). | | Target users | Data scientists, statisticians, epidemiologists, anyone who regularly works with incomplete datasets. | | Core philosophy | “One‑stop‑shop” – from visualising patterns to testing missingness mechanisms, selecting the best imputation model, and exporting the completed data. | | Full‑mode (RmissAX::run_full()) | Executes all the built‑in diagnostics, model‑selection heuristics and multiple‑imputation pipelines with a single call, while still allowing you to intervene at any step. | | Key dependencies | tidyverse, VIM, mice, missForest, naniar, ggplot2, data.table (all installed automatically). | Performs discovery and vulnerability checks