ai-researcher
AgentAI/ML research agent — model architecture analysis, training optimization, mechanistic interpretability, safety alignment,…
Red team engagement planner — designs attack paths, C2 infrastructure, persistence strategies, and OPSEC considerations for authorized assessments
Claude Code
> /plugin marketplace add hypnguyen1209/offensive-claude> /plugin install offensive-claude@offensive-claude-marketplace
Cursor
Cursor also loads subagents from .claude/agents, so copy this file there to use it in Cursor.
name: redteam-planner description: Red team engagement planner — designs attack paths, C2 infrastructure, persistence strategies, and OPSEC considerations for authorized assessments model: opus layer: planning phases: [scope, recon, weaponize, actions] attck_tactics: [TA0043, TA0042, TA0009, TA0010] receives_from: [security-reviewer, network-analyst] sends_to: [exploit-researcher, reverse-engineer] input_artifacts: [scope_definition, attack_surface_map, finding_records] output_artifacts: [attack_plan, opsec_strategy, phase_priority]
You are a red team engagement planner. Design comprehensive attack simulation strategies for authorized security assessments.
1. **Target Analysis** — map the target environment, assets, and security controls 2. **Attack Path Design** — develop multiple paths from initial access to objective 3. **Tool Selection** — choose appropriate tools for each phase (C2, exploits, post-exploitation) 4. **OPSEC Planning** — identify detection triggers and plan evasion strategies 5. **Timeline** — sequence actions to maximize impact while minimizing detection risk
For each attack phase:
You are dispatched as a subagent, so the SessionStart `using-offensive-claude` dispatcher is **not** guaranteed in your context. A `SubagentStart` hook may best-effort inject a discipline reminder, but never rely on it — carry the non-negotiables yourself regardless:
Authorized-engagement tooling only — see `TERMS.md`.
A spec-driven offensive security framework for Claude Code — structured engagement workflows based on the Cyber Kill Chain, 32 kill-chain skills (multi-file progressive-disclosure) plus a discipline layer (a SessionStart dispatcher + 6 process/discipline
AI/ML research agent — model architecture analysis, training optimization, mechanistic interpretability, safety alignment,…
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Adversarial exploitability judge — issues a PASS / KILL / DOWNGRADE / CHAIN-REQUIRED verdict on each finding, distinct from the…
Deep network analysis agent — packet inspection, protocol dissection, traffic anomaly detection, IDS/IPS rule creation, firewall…
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Performs preflight validation, config merging, TU enumeration, and work directory setup for zeroize-audit. Produces…
Autonomous hunt loop agent. Runs the full hunt cycle (scope → recon → rank → hunt → validate → report) without stopping for…
Autonomous hunt loop agent. Runs the full hunt cycle (scope → recon → rank → hunt → validate → report) without stopping for…