crowdsec

A skill for installing, configuring, operating, and troubleshooting CrowdSec, a security tool that detects suspicious activity and can block it. It covers the local engine, its APIs, detection rules, integrations, and web-application firewall setup.

In plain words
What is it for?
Use it to install or upgrade CrowdSec, configure log collection and detection, connect firewalls or web servers, deploy its web-application firewall, troubleshoot alerts, or migrate from fail2ban.
Why use it?
CrowdSec has many parts, and problems such as logs not being parsed or blocked traffic not reaching a firewall can be difficult to diagnose. This provides guidance for day-to-day setup and maintenance.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/crowdsecurity/crowdsec-skill/crowdsec
Any agent
npx skills add crowdsecurity/crowdsec-skill --skill crowdsec
Clone the repo
git clone --depth 1 https://github.com/crowdsecurity/crowdsec-skill

Made for: Claude Code, Codex.

Per session 118 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,805 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00118 $0.03805
Opus 5 $0.00059 $0.01903
Sonnet 5 $0.00024 $0.00761
Haiku 4.5 $0.00012 $0.00380

Measured 2d ago against content hash 918db90fd205, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

crowdsec scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/check-verification.py, scripts/diagnose.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

id -u # 0 = root; otherwise the user needs sudo ```

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -s https://version.crowdsec.net/latest # → {"tag_name":"v1.7.8",...}; parse tag_name
skills/crowdsec/SKILL.md · 196 lines

How it starts

The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CrowdSec — operations, deployment, configuration, and debugging

Glossary: AppSec is the engine component name (in configs, hub paths, cscli appsec-*, Helm workload); WAF is the user-facing term for the same thing. This skill uses both interchangeably.

Boundary — what this skill does and does not do

You want to… Use
Install / upgrade / uninstall CrowdSec this skill
Configure acquisition, hub, profiles, notifications this skill
Install and wire a bouncer (firewall, nginx, traefik, caddy) this skill
Deploy the WAF (AppSec component) this skill
Debug "logs not parsing" / "no alerts" / "bouncer not blocking" this skill
Migrate from fail2ban this skill
Write a parser, scenario, or WAF (AppSec) rule the crowdsec-local-mcp mcp
Drive the cloud Service API (manage blocklists / allowlists / firewall integrations / metrics / decisions programmatically) the crowdsec-service-api skill

Step 1 — Detect the environment

Run probes in this order. Stop at the first match.

# systemd / bare-metal
systemctl list-unit-files crowdsec.service >/dev/null 2>&1 && systemctl is-enabled crowdsec >/dev/null 2>&1
# docker
docker ps --format '{{.Names}} {{.Image}}' 2>/dev/null | grep -E '(^|/)(crowdsec)([: ]|$)'
# kubernetes
kubectl get pods -A 2>/dev/null | grep -i crowdsec

If nothing matches and the user reports CrowdSec is installed, ask where: a vendor appliance, a custom image, a binary in /opt/, or a remote host. Otherwise pivot to install: see references/install/.

pfSense detection:

uname -i   # → pfSense  (pfSense CE or Plus)

If confirmed pfSense, go directly to references/install/pfsense.md — paths, service names, and activation flow are entirely different from Linux/systemd.

Privileges — bare-metal / systemd prerequisite

On bare-metal/systemd, cscli and crowdsec need root (they read /etc/crowdsec/, the DB under /var/lib/crowdsec/, and control the systemd unit). Before running anything that touches config or state, confirm the user is root or has sudo:

Read the full file on GitHub · 196 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 196 lines · 118 tokens per session scan B 918db90fd205

Subscribe to this mod's changes

crowdsec is a skill published in the GitHub repository crowdsecurity/crowdsec-skill (23 stars, last pushed 14d ago), licensed MIT. It adds 118 tokens to every session and 3,805 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens