mass-assignment

mass-assignment is a skill for Claude Code, Codex from PurpleAILAB/Decepticon. It costs 28 tokens per session (1,250 once invoked), scanned A, original, Apache-2.0.

A security testing guide for mass assignment, where an API accepts extra fields and lets users change protected account data. It also covers ORM leaks, where database fields are exposed in API responses.

In plain words
What is it for?
Use it to review JSON create and update requests, model binding, profile endpoints, and API response filtering.
Why use it?
It helps find ways to grant administrator rights, alter balances or permissions, or reveal private fields.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review JSON create and update requests, model binding, profile endpoints, and API response filtering.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/purpleailab/decepticon/mass-assignment
About the project

Decepticon is an autonomous red-team agent that coordinates AI agents, security tools, sandboxes, and supporting services for authorized cybersecurity assessments. Security researchers and red teams can run it through its Docker stack, cloud service, command-line interface, or Python SDK, with the catalogue entries representing its available skills.

PurpleAILAB/Decepticon · 5,491 stars · on GitHub · decepticon.red

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.

Any agent
npx skills add PurpleAILAB/Decepticon --skill mass-assignment
Clone the repo
git clone --depth 1 https://github.com/PurpleAILAB/Decepticon

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mass-assignment

README.md
[![agentmods](https://agentmods.dev/badge/skills/purpleailab/decepticon/mass-assignment/github.svg)](https://agentmods.dev/skills/purpleailab/decepticon/mass-assignment)
Your own site
<a href="https://agentmods.dev/skills/purpleailab/decepticon/mass-assignment"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/mass-assignment/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mass-assignment

Your own site · 80×15
<a href="https://agentmods.dev/skills/purpleailab/decepticon/mass-assignment"><img src="https://agentmods.dev/badge/skills/purpleailab/decepticon/mass-assignment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,250 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 100
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
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 5.1 $0.00028 $0.01250
Opus 5 $0.00014 $0.00625
Sonnet 5 $0.00006 $0.00250
Haiku 4.5 $0.00003 $0.00125

Measured 9d ago against content hash 6a4f73412020, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

mass-assignment scanned grade A with 1 finding 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 9d ago.

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.

Makes network callslowCapability

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

r = requests.post(f"{TARGET}/register", json={
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

packages/decepticon/decepticon/skills/standard/exploit/web/mass-assignment/SKILL.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Mass Assignment + ORM Leak

API endpoints that bind request JSON straight to model update() / create() without an allowlist can be coerced into setting admin fields (is_admin, role, verified, etc).

1. Detect

# Capture a legitimate update request
PATCH /api/users/me
{"name": "Alice"}

# Try adding common privileged fields
PATCH /api/users/me
{"name": "Alice", "is_admin": true, "role": "admin", "verified": true,
 "balance": 999999, "permissions": ["*"], "isStaff": true,
 "membership_level": "premium", "tier": "enterprise"}

Re-fetch own profile. If any of the injected fields persists with attacker-set value → mass assignment.

2. Common field names to try

is_admin  isAdmin  admin  superuser  is_staff  isStaff  staff
role  roles  permission  permissions  scope  scopes  group  groups
verified  email_verified  isVerified  approved  banned  is_banned
balance  credits  points  reputation
tier  membership_level  plan  subscription
created_at  email  user_id  uuid  external_id  organization_id
password  password_hash

3. Framework-specific patterns

Rails (legacy, pre-strong-params)

User.create(params[:user]) → all params mass-assigned. Rails 4+ enforces params.require(:user).permit(:name, :email). If permit list is too broad, mass assignment.

Django REST Framework

UserSerializer(instance, data=request.data, partial=True).save() → all declared fields settable. Bug: developer adds is_staff to serializer fields by mistake.

Express / Mongoose

User.findOneAndUpdate({_id: req.params.id}, req.body)
// → any req.body field becomes a $set. Catastrophic.

Spring Boot

@RequestBody User u → Jackson binds all settable properties. If User has setter for role, attacker can set it.

Go / Echo / Gin

c.Bind(&user) → same pattern.

4. ORM Leak — the response side

Sometimes the response serializer leaks fields the request can't set:

GET /api/users/123
{
  "id": 123,
  "name": "Alice",
  "email": "[email protected]",
  "password_hash": "$2a$12$...",       ← leak!
  "totp_secret": "JBSW...",            ← leak!
  "stripe_customer_id": "cus_...",
  "internal_notes": "VIP customer"
}

Read the full file on GitHub · 154 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. 9d ago First seen · 154 lines · 28 tokens per session scan A 6a4f73412020

Subscribe to this mod's changes

mass-assignment is a skill published in the GitHub repository PurpleAILAB/Decepticon (5,491 stars, last pushed 13d ago), licensed Apache-2.0. It adds 28 tokens to every session and 1,250 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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