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Django Access Review

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getsentry
django-access-review

Django access control and IDOR security review. Use when reviewing Django views, DRF viewsets, ORM queries, or any Python/Django code handling user authorization. Trigger keywords: "IDOR", "access control", "authorization", "Django permissions", "object permissions", "tenant isolation", "broken access".

Overview

Publishergetsentry
Repositoryskills
Skill namedjango-access-review
Stars
1K
Forks
53
Bundled files
4
LicenseLICENSE
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Django Access Review 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.
    https://github.com/getsentry/skills/tree/main/skills/django-access-review
  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/getsentry/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/django-access-review .claude/skills/django-access-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Django Access Review 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 Django Access Review 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 Django Access Review 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.

Django Access Control & IDOR Review

Find access control vulnerabilities by investigating how the codebase answers one question:

Can User A access, modify, or delete User B's data?

Philosophy: Investigation Over Pattern Matching

Do NOT scan for predefined vulnerable patterns. Instead:

  1. Understand how authorization works in THIS codebase
  2. Ask questions about specific data flows
  3. Trace code to find where (or if) access checks happen
  4. Report only what you've confirmed through investigation

Every codebase implements authorization differently. Your job is to understand this specific implementation, then find gaps.


Phase 1: Understand the Authorization Model

Before looking for bugs, answer these questions about the codebase:

How is authorization enforced?

Research the codebase to find:

□ Where are permission checks implemented?
  - Decorators? (@login_required, @permission_required, custom?)
  - Middleware? (TenantMiddleware, AuthorizationMiddleware?)
  - Base classes? (BaseAPIView, TenantScopedViewSet?)
  - Permission classes? (DRF permission_classes?)
  - Custom mixins? (OwnershipMixin, TenantMixin?)

□ How are queries scoped?
  - Custom managers? (TenantManager, UserScopedManager?)
  - get_queryset() overrides?
  - Middleware that sets query context?

□ What's the ownership model?
  - Single user ownership? (document.owner_id)
  - Organization/tenant ownership? (document.organization_id)
  - Hierarchical? (org -> team -> user -> resource)
  - Role-based within context? (org admin vs member)

Investigation commands

bash
# Find how auth is typically done
grep -rn "permission_classes\|@login_required\|@permission_required" --include="*.py" | head -20

# Find base classes that views inherit from
grep -rn "class Base.*View\|class.*Mixin.*:" --include="*.py" | head -20

# Find custom managers
grep -rn "class.*Manager\|def get_queryset" --include="*.py" | head -20

# Find ownership fields on models
grep -rn "owner\|user_id\|organization\|tenant" --include="models.py" | head -30

Do not proceed until you understand the authorization model.


Phase 2: Map the Attack Surface

Identify endpoints that handle user-specific data:

What resources exist?

□ What models contain user data?
□ Which have ownership fields (owner_id, user_id, organization_id)?
□ Which are accessed via ID in URLs or request bodies?

What operations are exposed?

For each resource, map:

  • List endpoints - what data is returned?
  • Detail/retrieve endpoints - how is the object fetched?
  • Create endpoints - who sets the owner?
  • Update endpoints - can users modify others' data?
  • Delete endpoints - can users delete others' data?
  • Custom actions - what do they access?

Phase 3: Ask Questions and Investigate

For each endpoint that handles user data, ask:

The Core Question

"If I'm User A and I know the ID of User B's resource, can I access it?"

Trace the code to answer this:

1. Where does the resource ID enter the system?
   - URL path: /api/documents/{id}/
   - Query param: ?document_id=123
   - Request body: {"document_id": 123}

2. Where is that ID used to fetch data?
   - Find the ORM query or database call

3. Between (1) and (2), what checks exist?
   - Is the query scoped to current user?
   - Is there an explicit ownership check?
   - Is there a permission check on the object?
   - Does a base class or mixin enforce access?

4. If you can't find a check, is there one you missed?
   - Check parent classes
   - Check middleware
   - Check managers
   - Check decorators at URL level

Follow-Up Questions

□ For list endpoints: Does the query filter to user's data, or return everything?

□ For create endpoints: Who sets the owner - the server or the request?

□ For bulk operations: Are they scoped to user's data?

□ For related resources: If I can access a document, can I access its comments?
  What if the document belongs to someone else?

□ For tenant/org resources: Can User in Org A access Org B's data by changing
  the org_id in the URL?

Phase 4: Trace Specific Flows

Pick a concrete endpoint and trace it completely.

Example Investigation

Endpoint: GET /api/documents/{pk}/

1. Find the view handling this URL
   → DocumentViewSet.retrieve() in api/views.py

2. Check what DocumentViewSet inherits from
   → class DocumentViewSet(viewsets.ModelViewSet)
   → No custom base class with authorization

3. Check permission_classes
   → permission_classes = [IsAuthenticated]
   → Only checks login, not ownership

4. Check get_queryset()
   → def get_queryset(self):
   →     return Document.objects.all()
   → Returns ALL documents!

5. Check for has_object_permission()
   → Not implemented

6. Check retrieve() method
   → Uses default, which calls get_object()
   → get_object() uses get_queryset(), which returns all

7. Conclusion: IDOR - Any authenticated user can access any document

What to look for when tracing

Potential gap indicators (investigate further, don't auto-flag):
- get_queryset() returns .all() or filters without user
- Direct Model.objects.get(pk=pk) without ownership in query
- ID comes from request body for sensitive operations
- Permission class checks auth but not ownership
- No has_object_permission() and queryset isn't scoped

Likely safe patterns (but verify the implementation):
- get_queryset() filters by request.user or user's org
- Custom permission class with has_object_permission()
- Base class that enforces scoping
- Manager that auto-filters

Phase 5: Report Findings

Only report issues you've confirmed through investigation.

Confidence Levels

LevelMeaningAction
HIGHTraced the flow, confirmed no check existsReport with evidence
MEDIUMCheck may exist but couldn't confirmNote for manual verification
LOWTheoretical, likely mitigatedDo not report

Suggested Fixes Must Enforce, Not Document

Bad fix: Adding a comment saying "caller must validate permissions" Good fix: Adding code that actually validates permissions

A comment or docstring does not enforce authorization. Your suggested fix must include actual code that:

  • Validates the user has permission before proceeding
  • Raises an exception or returns an error if unauthorized
  • Makes unauthorized access impossible, not just discouraged

Example of a BAD fix suggestion:

python
def get_resource(resource_id):
    # IMPORTANT: Caller must ensure user has access to this resource
    return Resource.objects.get(pk=resource_id)

Example of a GOOD fix suggestion:

python
def get_resource(resource_id, user):
    resource = Resource.objects.get(pk=resource_id)
    if resource.owner_id != user.id:
        raise PermissionDenied("Access denied")
    return resource

If you can't determine the right enforcement mechanism, say so - but never suggest documentation as the fix.

Report Format

markdown
## Access Control Review: [Component]

### Authorization Model
[Brief description of how this codebase handles authorization]

### Findings

#### [IDOR-001] [Title] (Severity: High/Medium)
- **Location**: `path/to/file.py:123`
- **Confidence**: High - confirmed through code tracing
- **The Question**: Can User A access User B's documents?
- **Investigation**:
  1. Traced GET /api/documents/{pk}/ to DocumentViewSet
  2. Checked get_queryset() - returns Document.objects.all()
  3. Checked permission_classes - only IsAuthenticated
  4. Checked for has_object_permission() - not implemented
  5. Verified no relevant middleware or base class checks
- **Evidence**: [Code snippet showing the gap]
- **Impact**: Any authenticated user can read any document by ID
- **Suggested Fix**: [Code that enforces authorization - NOT a comment]

### Needs Manual Verification
[Issues where authorization exists but couldn't confirm effectiveness]

### Areas Not Reviewed
[Endpoints or flows not covered in this review]

Common Django Authorization Patterns

These are patterns you might find - not a checklist to match against.

Query Scoping

python
# Scoped to user
Document.objects.filter(owner=request.user)

# Scoped to organization
Document.objects.filter(organization=request.user.organization)

# Using a custom manager
Document.objects.for_user(request.user)  # Investigate what this does

Permission Enforcement

python
# DRF permission classes
permission_classes = [IsAuthenticated, IsOwner]

# Custom has_object_permission
def has_object_permission(self, request, view, obj):
    return obj.owner == request.user

# Django decorators
@permission_required('app.view_document')

# Manual checks
if document.owner != request.user:
    raise PermissionDenied()

Ownership Assignment

python
# Server-side (safe)
def perform_create(self, serializer):
    serializer.save(owner=self.request.user)

# From request (investigate)
serializer.save(**request.data)  # Does request.data include owner?

Investigation Checklist

Use this to guide your review, not as a pass/fail checklist:

□ I understand how authorization is typically implemented in this codebase
□ I've identified the ownership model (user, org, tenant, etc.)
□ I've mapped the key endpoints that handle user data
□ For each sensitive endpoint, I've traced the flow and asked:
  - Where does the ID come from?
  - Where is data fetched?
  - What checks exist between input and data access?
□ I've verified my findings by checking parent classes and middleware
□ I've only reported issues I've confirmed through investigation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Django Access Review AI skill do?

Django access control and IDOR security review. Use when reviewing Django views, DRF viewsets, ORM queries, or any Python/Django code handling user authorization. Trigger keywords: "IDOR", "access control", "authorization", "Django permissions", "object permissions", "tenant isolation", "broken access".

Why use Django Access Review on TypingMind?

Because you install it once and use it with any model. Django Access Review 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 Django Access Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getsentry/skills/tree/main/skills/django-access-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Django Access Review?

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 Django Access Review?

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

Is the Django Access Review AI skill free?

Yes. It is published on GitHub by getsentry under the LICENSE 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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