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Find Security Vulnerabilities In Code

OrganizationPopular
usestrix
find-security-vulnerabilities-in-code

Find security vulnerabilities in a codebase or repository with Strix — a white-box AI security review that reads your source, reasons about the actual data flow and authorization model, then exploits what it finds in a live sandbox so every reported issue has a working proof-of-concept instead of a noisy static-analysis alert. Covers injection, XSS, SSRF, broken access control and IDOR, insecure deserialization, secrets in code, unsafe dependencies, and business-logic flaws. Use when the user asks to security-scan, security-review, or audit their code, repo, or pull request for vulnerabilities.

Overview

Publisherusestrix
Repositorystrix
Skill namefind-security-vulnerabilities-in-code
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 Find Security Vulnerabilities In Code 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/find-security-vulnerabilities-in-code .claude/skills/find-security-vulnerabilities-in-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find Security Vulnerabilities In Code 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 Find Security Vulnerabilities In Code 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 Find Security Vulnerabilities In Code 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.

Find security vulnerabilities in code

White-box security review with Strix: the agents read the source to build a model of routes, sinks, and authorization checks, then attempt real exploitation. Findings come with a proof-of-concept, so the output is a short list of proven issues rather than the hundreds of "potential" hits a pattern-matching scanner produces.

Install, LLM setup, all flags, and the managed-cloud path are in the penetration-testing-with-strix skill. 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).

Run it

bash
# Local working tree
strix -n -t ./ --scan-mode standard --max-budget 15

# A GitHub repo directly
strix -n -t https://github.com/org/app --max-budget 15

# Monorepo: point at the service that matters, not the whole tree
strix -n -t ./services/checkout --max-budget 20

# Only what a branch changed (whole-repo review is wasteful on a large repo)
strix -n -t ./ --scope-mode diff --diff-base origin/main --max-budget 10

A local path is mounted into the sandbox writable, so the agents can modify it. Run against a clean checkout.

Two things sharply improve results:

  1. Add a running instance of the app. -t ./ -t http://host.docker.internal:3000 lets the agents confirm exploitability against live behavior instead of reasoning about it statically — this is the difference between "this looks unsafe" and a validated finding. If nothing is running, static-only findings should be described as unconfirmed.
  2. Scope the review. Point at the risky subtree and say what matters:
    bash
    strix -n -t ./services/api --max-budget 15 \
      --instruction "Focus on the authorization layer in src/auth and every route under src/routes/admin. Multi-tenant app: tenant id comes from the JWT. Flag any query that filters by object id without also filtering by tenant."
    Tenancy model, trust boundaries, and which inputs are attacker-controlled are things the agents cannot infer reliably — tell them.

Reviewing a pull request instead of the whole repo

For diff-scoped review of a branch or PR (and blocking merges on findings), use ci-security-scanning-with-strix — it covers diff scoping, PR comments, and SARIF upload to GitHub code scanning. The managed platform can also review PRs directly via API (managed-pentesting-with-strix).

Read the results

In strix_runs/<run>/: penetration_test_report.md (start here), vulnerabilities/*.md (one per finding, with PoC and remediation), vulnerabilities.json / .csv, findings.sarif (upload to code scanning), run.json.

Before reporting to the user, open each finding and check the PoC actually demonstrates impact. Report file and line alongside the exploit so the fix is obvious.

Exit 0 means nothing exploitable was proven in what was analyzed — not that the codebase is clean. Check run.json status and cost against --max-budget, and note which paths went unreviewed if the run was capped.

Complementary tooling

This is exploit-validated review, not an exhaustive inventory. Keep a dependency scanner (SCA) and secret scanning in place for complete coverage of known-CVE dependencies and committed credentials; use this for the logic, authorization, and injection bugs those tools structurally cannot find.

Fix and verify

Hand results to fix-security-vulnerabilities-with-strix: patch the root cause (the shared authorization helper, not the one route), then re-run Strix to prove the exploit no longer works.

Frequently asked questions

What does the Find Security Vulnerabilities In Code AI skill do?

Find security vulnerabilities in a codebase or repository with Strix — a white-box AI security review that reads your source, reasons about the actual data flow and authorization model, then exploits what it finds in a live sandbox so every reported issue has a working proof-of-concept instead of a noisy static-analysis alert. Covers injection, XSS, SSRF, broken access control and IDOR, insecure deserialization, secrets in code, unsafe dependencies, and business-logic flaws. Use when the user asks to security-scan, security-review, or audit their code, repo, or pull request for vulnerabilit...

Why use Find Security Vulnerabilities In Code on TypingMind?

Because you install it once and use it with any model. Find Security Vulnerabilities In Code 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 Find Security Vulnerabilities In Code in TypingMind?

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

Which AI models can use Find Security Vulnerabilities In Code?

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 Find Security Vulnerabilities In Code?

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

Is the Find Security Vulnerabilities In Code 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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