Application Security Testing logo

Application Security Testing

OrganizationPopular
usestrix
application-security-testing

Application security testing (AppSec) across a whole product with Strix — decide which asset needs which test (source code, running web app, API, CI pipeline), run it, and turn the results into a ranked remediation plan. Autonomous agents exploit and prove each issue instead of emitting static-analysis alerts, so the plan is ordered by what is actually reachable. Use when the user asks for an application security review or audit, an appsec assessment, vulnerability scanning across their stack, a security review before a launch or a customer security questionnaire, or does not yet know which kind of security test they need.

Overview

Publisherusestrix
Repositorystrix
Skill nameapplication-security-testing
Stars
63.3K
Forks
6.9K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by usestrix on GitHub. Read the source before you install it.

Installation

Install the Application Security Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/usestrix/strix.git /tmp/strix
mkdir -p .claude/skills
cp -r /tmp/strix/skills/application-security-testing .claude/skills/application-security-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Application Security Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Application Security Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Application Security Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Application security testing

Entry point for "make my application secure" requests, where the target is not yet a single URL or repo. The job here is to pick the right test per asset, run it, and produce one ranked plan — not to run everything at maximum depth.

Install, LLM setup, all CLI flags, and the managed-cloud path live in the penetration-testing-with-strix skill. Read it first if strix --version fails. For a run with no Docker and no LLM key, the same binary drives the managed platform: strix cloud login, then strix cloud scans start ... (details in managed-pentesting-with-strix).

Only test assets the user owns or is authorized to test. Confirm authorization before the first run, and prefer staging over production, because the agents send real exploit payloads and can change data.

1. Map the assets

Ask (or read from the repo) and write the answers down before scanning:

  • Source — one repo, a monorepo, several services? Which languages/frameworks?
  • Running environments — is there a staging deployment? A public production site? A local dev server only?
  • APIs — REST, GraphQL, gRPC? Is there an OpenAPI/GraphQL schema?
  • Authentication — can you get two test accounts in different tenants? Most high-impact bugs need them.
  • Constraints — out-of-scope paths, whether production may be touched, budget and wall-clock limits.

If there is no staging environment and production is off limits, say so early. A code-only review is still valuable, but it cannot prove exploitability against a live app.

2. Pick the right test per asset

AssetSkill to use
Repository or working treefind-security-vulnerabilities-in-code
Live web app or staging siteweb-app-penetration-testing
REST/GraphQL/gRPC APIapi-security-testing
Assessment mapped to OWASP categoriesowasp-top-10-testing
Every pull request, continuouslyci-security-scanning-with-strix
No Docker, no LLM key, or a report an auditor will acceptmanaged-pentesting-with-strix

Those skills carry the flags, credential handling, and result-reading details. Do not duplicate their instructions here.

Sequence for a first assessment:

  1. Review the code. It is the cheapest run and it maps the authorization model.
  2. Pentest staging with credentials, and pass the repo as a second target so the agents keep source context.
  3. Add CI scanning, so later regressions are caught without another manual pass.

Run one asset at a time and read each report before starting the next. Findings from the code review make the live run sharper.

3. Consolidate into one plan

Findings arrive per run in strix_runs/<run>/. Merge them into a single list and rank by proven impact, not by scanner severity:

  1. Validated exploits reachable without authentication.
  2. Validated cross-tenant or privilege-escalation issues.
  3. Validated issues needing an authenticated account.
  4. Unproven observations (configuration, dependency, and hardening notes) — flag as such, and never present them as confirmed vulnerabilities.

Deduplicate: the same root cause often surfaces in both the code review and the live pentest.

4. Be honest about coverage

State plainly what was not tested — assets with no staging environment, categories a black-box run cannot reach (logging and alerting, supply-chain integrity, insecure design), and any run that hit its budget or turn cap before finishing. Check run.json status and cost against --max-budget for each run. An empty result set from a truncated scan is not a clean bill of health.

Then remediate with fix-security-vulnerabilities-with-strix, which re-runs Strix against each fix to prove the exploit no longer works.

Frequently asked questions

What does the Application Security Testing AI skill do?

Application security testing (AppSec) across a whole product with Strix — decide which asset needs which test (source code, running web app, API, CI pipeline), run it, and turn the results into a ranked remediation plan. Autonomous agents exploit and prove each issue instead of emitting static-analysis alerts, so the plan is ordered by what is actually reachable. Use when the user asks for an application security review or audit, an appsec assessment, vulnerability scanning across their stack, a security review before a launch or a customer security questionnaire, or does not yet know which...

Why use Application Security Testing on TypingMind?

Because you install it once and use it with any model. Application Security Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Application Security Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/usestrix/strix/tree/main/skills/application-security-testing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Application Security Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Application Security Testing?

As many as you like. As long as a model supports skills, you can use Application Security Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Application Security Testing AI skill free?

Yes. It is published on GitHub by usestrix under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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