AI in Offensive Security

Complete setup guide: MCP configuration for Gemini, OpenAI, Cursor, and Ollama/Llama backends. First-run walkthrough and performance notes.

Strategic analysis of HexStrike AI's red team impact and the threat landscape implications when this level of automation becomes attacker-accessible.

Side-by-side comparison of two AI pentesting frameworks — architecture, autonomy level, output quality, and practical operator experience.

Local LLM setup: Ubuntu host + Kali VM + SSH bridging architecture for fully offline HexStrike AI operation. Performance benchmarks vs. cloud APIs.

Connecting Shodan's internet-wide exposure data into HexStrike's AI pipeline for automated attack surface enumeration and prioritization.

Full exploitation walkthrough against Metasploitable using HexStrike with OpenAI Codex — from scan to shell with AI-generated payload selection.

Full-scope Cursor + MCP methodology guide: tool selection, workflow design, scope controls, and the modern AI-augmented PT engagement lifecycle.

End-to-end home lab PT: HexStrike AI drives host discovery, service enumeration, vulnerability identification, and exploitation across a real local network.

AI-orchestrated web app PT: reconnaissance, fingerprinting, injection testing, authentication bypass, and finding synthesis with HexStrike + Gemini.

HexStrike AI drives a complete WiFi security assessment — capture, deauth, handshake collection, and password cracking — from a single natural-language prompt.

AI-driven SSH attack: target selection, credential list curation with Gemini, Hydra orchestration, and result synthesis — all via HexStrike MCP.

SMB exposure assessment and credential attack — Gemini CLI selects protocol parameters, HexStrike executes and interprets the brute-force results.

Full subnet compromise walkthrough: Cursor + HexStrike MCP chains host discovery, pivot identification, lateral movement, and credential extraction across a /24.

AI-driven OSINT from a single email address: Cursor orchestrates Shodan, theHarvester, passive DNS, and certificate data into a complete exposure map.

Complete AI-automated ADCS ESC8 exploitation: Cursor + HexStrike chain certificate discovery, ESC8 vulnerability identification, and domain compromise steps.

Three-tool AI stack: Cursor orchestrates HexStrike for infrastructure and Burp Suite MCP for web layers — coverage across cloud, API, and application attack surface.

Fully autonomous K8s PT from a single prompt: AI discovers cluster entry points, misconfigurations, privilege escalation paths, and lateral movement routes.

AI-orchestrated AD attack chain: Kerberoasting, AS-REP roasting, Pass-the-Hash, and LSASS dump — all driven from natural-language attack objectives.

HexStrike + Gemini CLI orchestrates wordlist generation, hash extraction, and John/Hashcat targeting for ZIP archives in an authorized recovery workflow.

DOC, DOCX, and PPT password recovery: Gemini CLI selects office2john extraction parameters and attack mode, HexStrike drives the cracking pipeline.

PDF owner/user password recovery: pdf2john hash extraction, Gemini-selected attack parameters, and Hashcat/John execution via HexStrike orchestration.

Connecting Burp Suite's MCP server to Gemini CLI for AI-driven web application security testing — automated crawl, active scan, and finding triage.

Overview and walkthrough of Villager — an autonomous AI PT framework that chains recon, exploitation, and reporting without human step-by-step input.

Using Cursor AI to generate, iterate, and deploy HID payloads on an Arduino Leonardo. Full workflow from payload concept to physical keystroke injection device.

Cursor AI as a hacker tool factory: generating and refining Android HID attack payloads, testing in an isolated lab, and iterating with AI feedback loops.

Documented experiment: generating functional malware using only natural-language prompts to AI coding tools. Implications for defender awareness and detection coverage.

AI-augmented Nmap recon: feeding scan output to ChatGPT for service fingerprinting interpretation, CVE context, and prioritized attack surface narrative.

LLM-augmented Burp workflow: using AI to interpret scanner findings, generate attack payloads, prioritize vulnerabilities, and draft pentest report sections.

HackerAI as a pentesting copilot: step-by-step guide using HackerAI to guide Metasploitable exploitation — where it helps, where it falls short.

ChatGPT applied to DFIR workflows: evidence triage, artifact correlation, timeline construction, and report generation acceleration for security investigators.

AuditAI build walkthrough: nine scanner modules, Claude integration, Dockerized deployment, and single-command vulnerability report generation.

StratusAI build and deployment: multi-cloud scanning across 16 attack modules, AI-generated attack chain synthesis, and prioritized remediation output.

AIDebug tool walkthrough: automated static analysis that feeds disassembly output to an LLM and returns natural-language function explanations and capability assessments.

Terminal-based AI APK analyzer: permission extraction, certificate inspection, string analysis, and AI-generated threat assessment for Android binaries.

Macro analysis of AI's impact across the full offensive lifecycle: how attack velocity, tradecraft variety, and barrier-to-entry change when AI becomes a standard tool.

Evidence-based review of documented threat actor AI adoption: phishing automation, malware generation, reconnaissance acceleration, and the detection implications.

Prompt injection, RAG poisoning, tool-call manipulation, and data exfiltration via AI agents. Practical attack scenarios against production-grade LLM deployments.

Defender-facing analysis: how AI offensive tempo and tradecraft variety break existing detection assumptions, and what coverage gaps open as a result.

Cursor AI as an infrastructure provisioner: generating, executing, and validating a full Windows AD lab deployment from a single natural-language specification.