security automation

Practical, Bash-first guide to AI-driven security on Linux: collect signals with journald/ps/ss (plus optional auditd/inotify), train a lightweight IsolationForest model in Python, score new data, and auto-block abusive IPs with nftables—then schedule it with cron or systemd. No SIEM required; includes install commands, ready-to-run scripts, tuning tips, and safe rollout advice.

Turn your Linux terminal firehose into signal with Bash-first AI. This hands-on guide ships four auditable automations: SSH/auth anomaly detection, Suricata alert dedup/prioritization, CLI phishing URL classifier, and process outlier hunting, using jq plus minimal Python. Includes install snippets, copy-paste scripts, cron/systemd production tips, and hardening guidance (baseline, thresholds, least privilege, observability).

Hands-on guide to AI DevSecOps on Linux using Bash and common CLI tools: make environments reproducible (venv, pinned deps, rootless podman), shift-left with pre-commit (shellcheck, bandit, semgrep, detect-secrets, pip-audit), scan containers with Trivy, generate SBOMs, sign images/models with cosign, and automate via a one-command CI script—reducing risk and easing audits without slowing teams.

Learn to automate security reporting: a Bash-first pipeline collects Lynis, Nmap, ClamAV, AIDE, and log data, converts it to JSON, and uses an OpenAI-compatible API to generate a concise, risk-ranked Markdown report delivered daily via cron/systemd and optional email. Includes install steps, scripts, data sanitization, handling large outputs, git-based deltas, and guidance on cloud vs local models and fail-safes.