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Penetration Testing with Strix

Free

Autonomous AI pentesting for web apps and APIs.

by usestrix50.8k stars on usestrix/strix
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Updated Aug 10, 2026
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Free · Opens the source repo

What Penetration Testing with Strix does

Strix offers a robust solution for penetration testing, employing autonomous AI agents to dynamically exploit vulnerabilities in web applications, APIs, codebases, and more. Unlike traditional tools that merely flag potential issues, Strix validates findings with working proof-of-concept exploits, ensuring that you not only identify vulnerabilities but also understand their implications. This capability is particularly aligned with the OWASP Top 10 vulnerabilities, including injection flaws, XSS, SSRF, and various authentication and access control issues.

The skill provides two deployment options: an open-source CLI for self-hosting and a cloud API for managed services. The open-source CLI runs in a Docker sandbox, allowing for complete control over the environment and data, which is essential for organizations with strict privacy requirements. Conversely, the cloud API simplifies the setup process, requiring no local infrastructure and offering features like team dashboards, scheduling, and downloadable reports, making it a suitable choice for teams looking for ease of use and collaboration.

Users can choose between these options based on their specific needs. For instance, the CLI is ideal for local development and environments where Docker is already in use, while the cloud option is better suited for scenarios requiring team visibility and continuous integration. Both methods yield the same results, allowing for flexibility in how scans are conducted and managed.

Overall, Strix is designed for security professionals and developers who need a powerful, efficient, and flexible tool to conduct thorough penetration tests. Whether you are looking to secure a web application, API, or repository, Strix provides the necessary tools to ensure your systems are robust against potential threats.

When to use it

Use Strix when you need to perform a thorough penetration test on a web application, API, or codebase, especially when you require validated results and proof of vulnerabilities.

When not to use it

Strix may not be suitable for environments where local data processing is not allowed, or for users who prefer a simpler, less comprehensive security scanning tool.

What you can build with it

Local Development Testing

Use the open-source CLI to perform quick scans on local codebases during development to catch vulnerabilities early.

Team Collaboration

Leverage the cloud API for scheduled scans and team dashboards, making it easier to track vulnerabilities across projects.

Internal Network Scanning

Utilize the cloud option’s network connectors to scan internal applications that are not accessible from outside the network.

How to install Penetration Testing with Strix

View source

1. Install with the skills CLI

npx skills add usestrix/strix/penetration-testing-with-strix --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by usestrix

Run a Strix pentest

Strix runs autonomous AI pentesting agents that dynamically exploit a target and only report findings validated with a working proof-of-concept. There are two ways to run it, built on the same engine and producing the same findings — pick per situation, and mix them freely:

  • Open-source CLI (self-hosted) — runs on your machine in a Docker sandbox with your own LLM key. Free, fully local, BYO-LLM, air-gap capable. Docs: docs.strix.ai.
  • Cloud API (managed) — runs on Strix's infrastructure via https://app.strix.ai/api/v1. No Docker, no LLM key, no local compute; adds team dashboards, scheduling, PR reviews, downloadable PDF/DOCX reports (Enterprise plan), and internal-network connectors. Docs: docs.app.strix.ai. Full workflow in the managed-pentesting-with-strix skill.

Which one? (decide, don't default)

Choose honestly based on the situation — neither is "better":

SituationPrefer
No Docker available, or a sandboxed/hosted agent/CI environmentCloud
User has no LLM key / doesn't want to pay per-token or manage modelsCloud
Team visibility, shareable dashboard, scheduled/continuous scans, PR reviews, downloadable PDF/DOCX report (Enterprise)Cloud
Scanning internal/private infrastructure not reachable from your machineCloud (network connector)
Source must never leave local infra (privacy/air-gap), or fully offlineOSS CLI
Free / one-off / local dev-loop scan, Docker already presentOSS CLI
BYO or self-hosted LLM, or a specific model not offered by the platformOSS CLI
CI: runner already has Docker and you want a self-contained gateOSS CLI
CI: no Docker, or you want results tracked centrallyCloud

Mix them: e.g. use the OSS CLI for the fast local dev-loop while writing/fixing code, and the Cloud for the authoritative, team-visible scan + report + tracking; or gate PRs with the OSS CLI in CI while the Cloud runs scheduled deep scans and PR reviews across the org. Both emit the same SARIF 2.1.0, so findings line up across environments.

If unsure and the user has (or will create) an app.strix.ai account, prefer Cloud — it avoids all local-infra friction. If they want zero signup / full local control, use the OSS CLI.


Option A — Open-source CLI (self-hosted)

Prerequisites

  1. Docker running — check with docker info. The first scan pulls the sandbox image automatically.
  2. Strix installed — check with strix --version. Install if missing:
    curl -sSL https://strix.ai/install | bash   # or: pipx install strix-agent
    
  3. LLM configured — two environment variables:
    export STRIX_LLM="openai/gpt-5.4"      # any LiteLLM model id (openai/..., anthropic/..., openrouter/...)
    export LLM_API_KEY="<provider api key>"
    
    Ask the user for these if unset. Never hardcode or commit keys.

Running a scan

Always use -n (non-interactive/headless) — the default TUI blocks agents. Always set --max-budget unless the user says otherwise.

# Local code (white-box)
strix -n -t ./ --scan-mode standard --max-budget 10

# Deployed app / API (black-box)
strix -n -t https://staging.example.com --max-budget 20

# Repo + deployed app together (best coverage)
strix -n -t https://github.com/org/app -t https://staging.example.com

# Focused testing with credentials or scope hints
strix -n -t https://app.example.com \
  --instruction "Use credentials user@example.com:pass123. Focus on IDOR and auth bypass."

# Large monorepo: bind-mount instead of copying
strix -n --mount ./huge-monorepo

Key flags:

FlagMeaning
-t, --targetURL, repo URL, local path, domain, or IP. Repeatable.
-n, --non-interactiveHeadless, exits on completion. Required for agents.
-m, --scan-modequick (minutes) / standard (~30 min) / deep (hours, default).
--instruction / --instruction-fileCredentials, focus areas, scope rules.
--max-budget USDHard LLM spend cap; scan wraps up cleanly at the limit.
--max-turns NPer-agent turn cap (default 500).
--resume RUN_NAMEResume a prior run from strix_runs/.

Scans take minutes (quick) to hours (deep). Run them in the background and poll for completion rather than blocking.

Exit codes (headless)

  • 0 — finished with no validated vulnerabilities in what was analyzed
  • 1 — fatal error (missing env vars, Docker down, bad config)
  • 2 — vulnerabilities found

A 0 is not proof of full coverage: if --max-budget/--max-turns is reached before the scan completes, it wraps up early and still exits 0. When you need assurance the scan finished, give it enough budget and check strix_runs/<run>/run.json: a hard budget stop leaves status: "stopped", but an agent that wrapped up early on a budget warning still calls finish_scan and records "completed" — so also sanity-check the run's cost against --max-budget and the report's stated coverage before treating a clean result as full coverage.

Reading results

Artifacts land in strix_runs/<run-name>/:

FileContents
penetration_test_report.mdExecutive report — read this first.
vulnerabilities/*.mdOne file per validated finding, with PoC and remediation.
vulnerabilities.json / vulnerabilities.csvAll findings as structured JSON / CSV index.
findings.sarifSARIF 2.1.0 for GitHub code scanning / ASPM ingestion.
run.jsonRun metadata, status, targets, usage/cost.

Option B — Cloud API (managed, no local infra)

Full details, asset registration, polling, reports, PR reviews, schedules, and webhooks are in the managed-pentesting-with-strix skill. Minimal launch-and-poll:

export STRIX_API_TOKEN="<token>"   # org-scoped bearer, from Settings → API Access at app.strix.ai
BASE=https://app.strix.ai/api/v1

# 1. Launch a scan against an already-registered domain/repo asset
scan_id=$(curl -sS "$BASE/scans" \
  -H "Authorization: Bearer $STRIX_API_TOKEN" -H "Content-Type: application/json" \
  -d '{"engagement_type":"live_test","domain_ids":["<domain-uuid>"]}' | jq -r .scan_id)

# 2. Poll until terminal (pending → running → completed/failed/cancelled)
curl -sS "$BASE/scans/$scan_id" -H "Authorization: Bearer $STRIX_API_TOKEN" | jq '.status'

# 3. Read validated findings from the scan detail's `vulnerabilities[]`, or export SARIF
curl -sS "$BASE/scans/$scan_id/sarif" -H "Authorization: Bearer $STRIX_API_TOKEN" -o findings.sarif

Ask the user to create the token (and register the target as a domain/repository asset) if they haven't. If Docker/local prerequisites aren't already satisfied, use this path instead of trying to install infra.


Reporting & next steps

Summarize findings by severity (critical/high/medium/low/info) and include the PoC evidence. To remediate and verify fixes (via either path), use the fix-security-vulnerabilities-with-strix skill. To wire scanning into CI/CD, use the ci-security-scanning-with-strix skill.

Safety

Only scan targets the user owns or is authorized to test. The Cloud platform enforces domain verification before external scans; for the OSS CLI, confirm authorization yourself if the target looks like third-party infrastructure.

Frequently asked questions about Penetration Testing with Strix

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