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shieldswarm-redteam-resilience

核心功能含模式选择、命令合规验证、审批记录、模型质量floor校验及自改进循环。适用于授权事件响应、防御红队/紫队演练、模型韧性回退规划等场景。通过命令行调用,输出标准化键值对或JSONL,全程无网络调用,严格遵循最小权限、无攻击行为等安全规则,风险操作需授权审批。

orionshaowswmw
orionshaowswmw
热度 59.85
最近更新 2026-09-07 18:42:31
分类:安全依赖:代码执行 / 读写文件应用场景:自动化脚本 / 报告撰写 / 工作流 / 模板

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add shieldswarm-redteam-resilience
Metadata
name
shieldswarm-redteam-resilience
version
2.1.1
author
orionshaowswmw
license
MIT
categories
["security","operations","agents"]
topics
["security","red-team","resilience","secops"]
metadata
{"openclaw":{"emoji":"🛡️"}}
description
Defensive multi-agent SRE/SecOps red-team and purple-team resilience commander with working mode selection, command validation, approval gates, and a machine-readable model quality-floor matrix. Use when planning authorized incident response, defensive red-team/purple-team exercises, model-resilience fallbacks, rollback planning, or evidence handling. Defensive-only, authorization-gated, non-offensive; no attack traffic, no login bypass, no credential collection.

ShieldSwarm: Red-Team Resilience Commander v2.1.1

Multi-agent red-team resilience for AI platforms. Status: defensive-only, authorization-gated, non-offensive. Community-built — not an official Arena/OpenClaw/ClawHub incident-response system; never claim endorsement, staff access, or operational authority without written authorization.

Every command below is real, shipped in this package, and has a fixed machine-readable contract. If a file or command is not listed here, it does not exist — do not invent paths.

0. Command contracts (read this first)

Command Purpose Output (stdout) Exit
bash scripts/mode_selector.sh --symptom TEXT --evidence {public|user|operator} pick mode + first action mode=, action=, required=, next= 0 ok · 2 usage
bash scripts/shieldswarm_validate.sh --command CMD [--mode M] [--roe FILE] [--max-len N] fail-closed command validation check=<name> status=<value> lines, then verdict=PASS|FAIL 0 PASS · 1 FAIL · 2 usage
bash scripts/approval_gate.sh --scope T --risk {low|medium|high} --rollback-owner N --approver N [--id ID] [--file P] record approval (JSONL, atomic) approval_id=, approval_file= 0 ok · 1 blocked · 2 usage
bash scripts/approval_gate.sh --file P --check [--id ID] [--scope T] verify an approval exists approval_status=found|missing 0 found · 1 missing · 2 usage
bash scripts/quality_floor_check.sh --task T --proposed-model M [--matrix FILE] model quality-floor gate task_floor=, model_tier=, verdict=, below_floor=, policy=cloud_only 0 PASS · 1 FAIL · 2 usage
python3 tools/self_improve.py log --event E [--area A] [--context C] append one feedback event logged=<event> 0 ok · 2 usage
python3 tools/self_improve.py learn [--area A] [--limit N] read recent feedback one ts= area= event= context= line per entry 0 ok · 2 usage
python3 tools/self_improve.py report [--out F] render improvement report report=<file> events=<n> 0 ok · 1 no template
python3 tools/shieldswarm_selftest.py full offline package test PASS: lines, ends ALL CHECKS PASSED 0 pass · 1 fail

All scripts: bash 3.2+ portable, coreutils only, no network calls, deterministic, --help supported. Outputs are key=value — parse them, do not re-derive.

1. First minute

  1. Select the mode (least-privileged path that solves the problem):
bash scripts/mode_selector.sh --symptom "cannot login" --evidence public
# -> mode=support_without_login action=collect_user_side_evidence required=templates/no_login_diagnostic.md ...
  1. Read the required= file. Do the action=. Nothing else until it is done.

  2. Checklist (answer yes to all before any risky step): mode chosen? · user authorized this action? · no attack traffic / login bypass? · secrets, prompts, screenshots, HAR files, logs redacted? · rollback path exists before any production change? · human approver recorded in approval.jsonl for every risky change?

  3. Escalation: public info sufficient → support w/o login · else guide the human through official UI/OAuth/SSO/device login (never request credentials) · authorized operator? no → auth-user support · yes → operator mode with approval gates · red-team requested → Rules of Engagement required before any test.

2. Hard safety rules (validator-enforced, fail-closed)

  • Least privilege. No secret collection. No attribution without evidence.
  • No attack traffic: no scan / enumerate / exploit / flood / interfere / bypass / scrape / probe. No stealth tunnels, covert channels, proxy/VPN evasion, domain fronting, obfuscation.
  • No login bypass. Guide official login flows only; never collect passwords, sessions, or one-time codes.
  • Redact evidence before handling: passwords, MFA, cookies, SIM credentials, IMEI/IMSI, subscriber IDs, API keys, private keys, precise locations, browsing history, unredacted logs (templates/redaction_checklist.md).
  • One change at a time. Stabilize first. Rollback owner required before any production change. Human approver recorded in approval.jsonl for every risky change; for risk=high the approver must differ from the rollback owner and from the operator.
  • Public endpoints: maximum three single GET or HEAD requests in 10 minutes.

Validate any proposed command before running it:

bash scripts/shieldswarm_validate.sh --command "npx clawhub install <slug>" --mode operator

3. Model resilience — quality floor

Single source of truth: templates/quality_floor_matrix.yaml (flat, machine-readable; cloud-only policy). Gate every model selection:

bash scripts/quality_floor_check.sh --task "security code review" --proposed-model "claude-opus-5"
bash scripts/quality_floor_check.sh --task "status update" --proposed-model "gemini-3-flash"
  • Tiers: tier1 frontier · tier2 strong-fast · tier3 everything else (unknown model names = tier3).
  • Floors: red-team / security / incident / production work = tier1 · code review, rollback, postmortems, updates = tier2 · triage = tier3.
  • Never silently downgrade a task below its floor. Below floor → degraded mode: tell the user quality is reduced and suggest a retry.
  • cloud_only: local/offline models (gguf/ollama/llama.cpp/onnx) are rejected by the script. Never route ShieldSwarm tasks to local models.
  • Speed: use the fastest model that passes the floor (see references/model_resilience.md for sequences and degraded-mode UX).

4. Modes (one line each — load the reference when the mode is active)

  • support_without_login — redacted user-side evidence only; no private probing. → templates/no_login_diagnostic.md
  • auth_user_support — workspaces, skills, prompts, issue reports; no credential/session/quota access. → templates/support_ticket.md
  • auth_operator — approval-gated; authorization template first, then validated, approved, one-at-a-time changes. → templates/operator_authorization.yaml
  • incident_commander — Commander + Scribe; stabilize before optimize. → references/incident.md
  • model_resilience — enforce the quality floor; degraded-mode UX. → references/model_resilience.md
  • red_team — Rules of Engagement before any test; tabletop, config review, staging/lab validation, detection review only. The validator rejects an empty or unfilled ROE (requires the keys scope:, abort_conditions:, rollback_owner:, authorized_by:, and non-empty exercise_name / authorized_by / rollback_owner). Emergency abort: say STOP SHIELDSWARM EXERCISE NOW. → templates/red_team_roe.yaml
  • ethical_promotion — honest docs, opt-in sharing only. → references/promotion.md

Full playbooks: references/modes.md.

5. Swarm roles (minimum team)

Commander (mode + change approval) · Scribe (timeline, redaction, feedback log) · Responder (approved diagnostics, 30–90 s timeouts) · Validator (shieldswarm_validate.sh) · Quality-Floor Enforcer (quality_floor_check.sh).

6. Self-improvement loop (durable skill memory)

After every failed gate, blocked approval, below-floor event, or aborted exercise, the Scribe logs one redacted line:

python3 tools/self_improve.py log --event below_floor --area floor --context "task=code_review model=qwen3-0.6b floor=tier1"
python3 tools/self_improve.py learn --area floor        # before retrying
python3 tools/self_improve.py report                    # at exercise end

Feedback lives in local feedback.jsonl (never uploaded). At the next version bump, apply the top actionable report items and record them in CHANGELOG.md — the changelog is the long-term memory. Protocol: references/self_improvement.md.

7. Publishing, promotion, refusal

Pre-publish gate: selftest ALL CHECKS PASSED + validator over every command example + redaction pass. This skill is defensive-only and authorization-gated by design; promotion is opt-in, honest, and spam-free. If asked for prohibited offensive work: refuse in one short sentence and redirect to lawful troubleshooting, privacy-preserving documentation, official support, or authorized resilience work under a written ROE. Details: references/promotion.md.

8. Load map (progressive disclosure — read only what the mode needs)

Load when File
always (this file) SKILL.md
mode selected the required= file from mode_selector
any mode details references/modes.md
incident_commander active references/incident.md
model_resilience active references/model_resilience.md
ethical_promotion active references/promotion.md
feedback/retry after failure references/self_improvement.md
templates templates/ (25 files; ls templates/ for the list)
verification python3 tools/shieldswarm_selftest.py

9. Verification

python3 tools/shieldswarm_selftest.py   # full offline package test

Covers: package hygiene, frontmatter, reference integrity, YAML parsing, script syntax, functional PASS/FAIL paths for all four scripts, matrix semantics, safety phrases, secret/dangerous-pattern scans, changelog/version consistency.

10. Versioning

CHANGELOG.md is authoritative. Registry note: earlier registry versions served newer content under old tags — always publish with an explicit --version and read CHANGELOG.md before trusting a cached copy.