security-hardening git:20260626.d01e4e4A

Immutable. This exact content is served forever at /api/v1/blob/74a614b89716d505.

---
name: security-hardening
description: Harden code against vulnerabilities. Use on triggers like "security audit", "harden this", "threat model", "is this safe", or when touching untrusted input, auth, sessions, secrets, data storage, or third-party integrations. Fills a security gap not covered by existing project skills. Not a generic review or ship workflow.
---

# Security and Hardening

## Overview

Security-first development practices for web applications. Treat every external input as hostile, every secret as sacred, and every authorization check as mandatory. Security isn't a phase — it's a constraint on every line of code that touches user data, authentication, or external systems.

## When to Use

- Building anything that accepts user input
- Implementing authentication or authorization
- Storing or transmitting sensitive data
- Integrating with external APIs or services
- Adding file uploads, webhooks, or callbacks
- Handling payment or PII data

## Process: Threat Model First

Controls bolted on without a threat model are guesses. Before hardening, spend five minutes thinking like an attacker:

1. **Map the trust boundaries.** Where does untrusted data cross into your system? HTTP requests, form fields, file uploads, webhooks, third-party APIs, message queues, and **LLM output**. Every boundary is attack surface.
2. **Name the assets.** What's worth stealing or breaking? Credentials, PII, payment data, admin actions, money movement.
3. **Run STRIDE over each boundary** — a quick lens, not a ceremony:

| Threat | Ask | Typical mitigation |
|---|---|---|
| **S**poofing | Can someone impersonate a user/service? | Authentication, signature verification |
| **T**ampering | Can data be altered in transit or at rest? | Integrity checks, parameterized queries, HTTPS |
| **R**epudiation | Can an action be denied later? | Audit logging of security events |
| **I**nformation disclosure | Can data leak? | Encryption, field allowlists, generic errors |
| **D**enial of service | Can it be overwhelmed? | Rate limiting, input size caps, timeouts |
| **E**levation of privilege | Can a user gain rights they shouldn't? | Authorization checks, least privilege |

4. **Write abuse cases next to use cases.** For each feature, ask "how would I misuse this?" — then make that your first test.

If you can't name the trust boundaries for a feature, you're not ready to secure it. This is OWASP **A04: Insecure Design** — most breaches begin in design, not code.

## The Three-Tier Boundary System

### Always Do (No Exceptions)

- **Validate all external input** at the system boundary (API routes, form handlers)
- **Parameterize all database queries** — never concatenate user input into SQL
- **Encode output** to prevent XSS (use framework auto-escaping, don't bypass it)
- **Use HTTPS** for all external communication
- **Hash passwords** with bcrypt/scrypt/argon2 (never store plaintext)
- **Set security headers** (CSP, HSTS, X-Frame-Options, X-Content-Type-Options)
- **Use httpOnly, secure, sameSite cookies** for sessions
- **Run `npm audit`** (or equivalent) before every release

### Ask First (Requires Human Approval)

- Adding new authentication flows or changing auth logic
- Storing new categories of sensitive data (PII, payment info)
- Adding new external service integrations
- Changing CORS configuration
- Adding file upload handlers
- Modifying rate limiting or throttling
- Granting elevated permissions or roles

### Never Do

- **Never commit secrets** to version control (API keys, passwords, tokens)
- **Never log sensitive data** (passwords, tokens, full credit card numbers)
- **Never trust client-side validation** as a security boundary
- **Never disable security headers** for convenience
- **Never use `eval()` or `innerHTML`** with user-provided data
- **Never store sessions in client-accessible storage** (localStorage for auth tokens)
- **Never expose stack traces** or internal error details to users

## OWASP Top 10 Prevention Patterns

These are prevention patterns, not a ranking. For the 2021 ordering, see the quick-reference table in `references/security-checklist.md`.

### Injection (SQL, NoSQL, OS Command)

```typescript
// BAD: SQL injection via string concatenation
const query = `SELECT * FROM users WHERE id = '${userId}'`;

// GOOD: Parameterized query
const user = await db.query('SELECT * FROM users WHERE id = $1', [userId]);

// GOOD: ORM with parameterized input
const user = await prisma.user.findUnique({ where: { id: userId } });
```

### Broken Authentication

```typescript
// Password hashing
import { hash, compare } from 'bcrypt';

const SALT_ROUNDS = 12;
const hashedPassword = await hash(plaintext, SALT_ROUNDS);
const isValid = await compare(plaintext, hashedPassword);

// Session management
app.use(session({
  secret: process.env.SESSION_SECRET,  // From environment, not code
  resave: false,
  saveUninitialized: false,
  cookie: {
    httpOnly: true,     // Not accessible via JavaScript
    secure: true,       // HTTPS only
    sameSite: 'lax',    // CSRF protection
    maxAge: 24 * 60 * 60 * 1000,  // 24 hours
  },
}));
```

### Cross-Site Scripting (XSS)

```typescript
// BAD: Rendering user input as HTML
element.innerHTML = userInput;

// GOOD: Use framework auto-escaping (React does this by default)
return <div>{userInput}</div>;

// If you MUST render HTML, sanitize first
import DOMPurify from 'dompurify';
const clean = DOMPurify.sanitize(userInput);
```

### Broken Access Control

```typescript
// Always check authorization, not just authentication
app.patch('/api/tasks/:id', authenticate, async (req, res) => {
  const task = await taskService.findById(req.params.id);

  // Check that the authenticated user owns this resource
  if (task.ownerId !== req.user.id) {
    return res.status(403).json({
      error: { code: 'FORBIDDEN', message: 'Not authorized to modify this task' }
    });
  }

  // Proceed with update
  const updated = await taskService.update(req.params.id, req.body);
  return res.json(updated);
});
```

### Security Misconfiguration

```typescript
// Security headers (use helmet for Express)
import helmet from 'helmet';
app.use(helmet());

// Content Security Policy
app.use(helmet.contentSecurityPolicy({
  directives: {
    defaultSrc: ["'self'"],
    scriptSrc: ["'self'"],
    styleSrc: ["'self'", "'unsafe-inline'"],  // Tighten if possible
    imgSrc: ["'self'", 'data:', 'https:'],
    connectSrc: ["'self'"],
  },
}));

// CORS — restrict to known origins
app.use(cors({
  origin: process.env.ALLOWED_ORIGINS?.split(',') || 'http://localhost:3000',
  credentials: true,
}));
```

### Sensitive Data Exposure

```typescript
// Never return sensitive fields in API responses
function sanitizeUser(user: UserRecord): PublicUser {
  const { passwordHash, resetToken, ...publicFields } = user;
  return publicFields;
}

// Use environment variables for secrets
const API_KEY = process.env.STRIPE_API_KEY;
if (!API_KEY) throw new Error('STRIPE_API_KEY not configured');
```

### Server-Side Request Forgery (SSRF)

Any time the server fetches a URL the user influenced — webhooks, "import from URL", image proxies, link previews — an attacker can aim it at internal services (cloud metadata, `localhost`, private IPs).

```typescript
// BAD: fetch whatever the user gives you
await fetch(req.body.webhookUrl);

// GOOD: allowlist scheme + host, reject if ANY resolved IP is private, forbid redirects
import { lookup } from 'node:dns/promises';
import ipaddr from 'ipaddr.js';

const ALLOWED_HOSTS = new Set(['hooks.example.com']);

async function assertSafeUrl(raw: string): Promise<URL> {
  const url = new URL(raw);
  if (url.protocol !== 'https:') throw new Error('https only');
  if (!ALLOWED_HOSTS.has(url.hostname)) throw new Error('host not allowed');
  // Resolve ALL records; a single private/reserved address fails the check.
  const addrs = await lookup(url.hostname, { all: true });
  if (addrs.some((a) => ipaddr.parse(a.address).range() !== 'unicast')) {
    throw new Error('private/reserved IP');
  }
  return url;
}

await fetch(await assertSafeUrl(req.body.webhookUrl), { redirect: 'error' });
```

The `range() !== 'unicast'` check covers loopback, link-local `169.254.169.254` (cloud metadata, the #1 SSRF target), private, and unique-local ranges across IPv4 and IPv6.

**Caveat — this still has a TOCTOU gap.** `fetch` resolves DNS again after the check, so an attacker using a short-TTL record can rebind to an internal IP between validation and connection. For high-risk surfaces, resolve once and connect to the pinned IP, or put a filtering agent in front (`request-filtering-agent` / `ssrf-req-filter`).

## Input Validation Patterns

### Schema Validation at Boundaries

```typescript
import { z } from 'zod';

const CreateTaskSchema = z.object({
  title: z.string().min(1).max(200).trim(),
  description: z.string().max(2000).optional(),
  priority: z.enum(['low', 'medium', 'high']).default('medium'),
  dueDate: z.string().datetime().optional(),
});

// Validate at the route handler
app.post('/api/tasks', async (req, res) => {
  const result = CreateTaskSchema.safeParse(req.body);
  if (!result.success) {
    return res.status(422).json({
      error: {
        code: 'VALIDATION_ERROR',
        message: 'Invalid input',
        details: result.error.flatten(),
      },
    });
  }
  // result.data is now typed and validated
  const task = await taskService.create(result.data);
  return res.status(201).json(task);
});
```

### File Upload Safety

```typescript
// Restrict file types and sizes
const ALLOWED_TYPES = ['image/jpeg', 'image/png', 'image/webp'];
const MAX_SIZE = 5 * 1024 * 1024; // 5MB

function validateUpload(file: UploadedFile) {
  if (!ALLOWED_TYPES.includes(file.mimetype)) {
    throw new ValidationError('File type not allowed');
  }
  if (file.size > MAX_SIZE) {
    throw new ValidationError('File too large (max 5MB)');
  }
  // Don't trust the file extension — check magic bytes if critical
}
```

## Triaging npm audit Results

Not all audit findings require immediate action. Use this decision tree:

```
npm audit reports a vulnerability
├── Severity: critical or high
│   ├── Is the vulnerable code reachable in your app?
│   │   ├── YES --> Fix immediately (update, patch, or replace the dependency)
│   │   └── NO (dev-only dep, unused code path) --> Fix soon, but not a blocker
│   └── Is a fix available?
│       ├── YES --> Update to the patched version
│       └── NO --> Check for workarounds, consider replacing the dependency, or add to allowlist with a review date
├── Severity: moderate
│   ├── Reachable in production? --> Fix in the next release cycle
│   └── Dev-only? --> Fix when convenient, track in backlog
└── Severity: low
    └── Track and fix during regular dependency updates
```

**Key questions:**
- Is the vulnerable function actually called in your code path?
- Is the dependency a runtime dependency or dev-only?
- Is the vulnerability exploitable given your deployment context (e.g., a server-side vulnerability in a client-only app)?

When you defer a fix, document the reason and set a review date.

### Supply-Chain Hygiene

`npm audit` catches known CVEs; it won't catch a malicious or typosquatted package. Also:

- **Commit the lockfile** and install with `npm ci` (not `npm install`) in CI — reproducible builds, no silent version drift.
- **Review new dependencies before adding them** — maintenance, download counts, and whether they truly earn their place. Every dependency is attack surface (OWASP **A06: Vulnerable Components**, **LLM03: Supply Chain**).
- **Be wary of `postinstall` scripts** in unfamiliar packages — they run arbitrary code at install time.
- **Watch for typosquats** — `cross-env` vs `crossenv`, `react-dom` vs `reactdom`.

## Rate Limiting

```typescript
import rateLimit from 'express-rate-limit';

// General API rate limit
app.use('/api/', rateLimit({
  windowMs: 15 * 60 * 1000, // 15 minutes
  max: 100,                   // 100 requests per window
  standardHeaders: true,
  legacyHeaders: false,
}));

// Stricter limit for auth endpoints
app.use('/api/auth/', rateLimit({
  windowMs: 15 * 60 * 1000,
  max: 10,  // 10 attempts per 15 minutes
}));
```

## Secrets Management

```
.env files:
  ├── .env.example  → Committed (template with placeholder values)
  ├── .env          → NOT committed (contains real secrets)
  └── .env.local    → NOT committed (local overrides)

.gitignore must include:
  .env
  .env.local
  .env.*.local
  *.pem
  *.key
```

**Always check before committing:**
```bash
# Check for accidentally staged secrets
git diff --cached | grep -i "password\|secret\|api_key\|token"
```

**If a secret is ever committed, rotate it.** Deleting the line or rewriting history is not enough — assume it's compromised the moment it reaches a remote. Revoke and reissue the key first, then purge it from history.

## Securing AI / LLM Features

If your app calls an LLM — chatbots, summarizers, agents, RAG — it inherits a new attack surface. Map it to the [OWASP Top 10 for LLM Applications (2025)](https://genai.owasp.org/llm-top-10/):

- **Treat all model output as untrusted input (LLM05: Improper Output Handling).** Never pass LLM output straight into `eval`, SQL, a shell, `innerHTML`, or a file path. Validate and encode it exactly as you would raw user input.
- **Assume prompts can be hijacked (LLM01: Prompt Injection).** Untrusted text in the context window — a user message, a fetched web page, a PDF — can carry instructions. The system prompt is not a security boundary; enforce permissions in code, not in the prompt.
- **Keep secrets and other users' data out of prompts (LLM02 / LLM07).** Anything in the context can be echoed back. Don't put API keys, cross-tenant data, or the full system prompt where the model can repeat it.
- **Constrain tool and agent permissions (LLM06: Excessive Agency).** Scope tools to the minimum, require confirmation for destructive or irreversible actions, and validate every tool argument.
- **Bound consumption (LLM10: Unbounded Consumption).** Cap tokens, request rate, and loop/recursion depth so a crafted input can't run up cost or hang the system.
- **Isolate retrieval data (LLM08: Vector and Embedding Weaknesses).** In RAG, treat the vector store as a trust boundary: partition embeddings per tenant so one user can't retrieve another's data, and validate documents before indexing so poisoned content can't steer answers.

```typescript
// BAD: trusting model output as a command or as markup
const sql = await llm.generate(`Write SQL for: ${userQuestion}`);
await db.query(sql);                                   // arbitrary query execution
container.innerHTML = await llm.reply(userMessage);   // stored XSS, via the model

// GOOD: model output is data — parse defensively, then validate, then encode
let intent;
try {
  intent = CommandSchema.parse(JSON.parse(await llm.replyJson(userMessage)));
} catch {
  throw new ValidationError('unexpected model output'); // JSON.parse or schema failed
}
await runAllowlistedAction(intent.action, intent.params);
container.textContent = await llm.reply(userMessage);
```

## Security Review Checklist

```markdown
### Authentication
- [ ] Passwords hashed with bcrypt/scrypt/argon2 (salt rounds ≥ 12)
- [ ] Session tokens are httpOnly, secure, sameSite
- [ ] Login has rate limiting
- [ ] Password reset tokens expire

### Authorization
- [ ] Every endpoint checks user permissions
- [ ] Users can only access their own resources
- [ ] Admin actions require admin role verification

### Input
- [ ] All user input validated at the boundary
- [ ] SQL queries are parameterized
- [ ] HTML output is encoded/escaped
- [ ] Server-side URL fetches are allowlisted (no SSRF to internal services)

### Data
- [ ] No secrets in code or version control
- [ ] Sensitive fields excluded from API responses
- [ ] PII encrypted at rest (if applicable)

### Infrastructure
- [ ] Security headers configured (CSP, HSTS, etc.)
- [ ] CORS restricted to known origins
- [ ] Dependencies audited for vulnerabilities
- [ ] Error messages don't expose internals

### Supply Chain
- [ ] Lockfile committed; CI installs with `npm ci`
- [ ] New dependencies reviewed (maintenance, downloads, postinstall scripts)

### AI / LLM (if used)
- [ ] Model output treated as untrusted (no eval/SQL/innerHTML/shell)
- [ ] Secrets and other users' data kept out of prompts
- [ ] Tool/agent permissions scoped; destructive actions require confirmation
```
## See Also

For detailed security checklists and pre-commit verification steps, see `references/security-checklist.md`.

## Common Rationalizations

| Rationalization | Reality |
|---|---|
| "This is an internal tool, security doesn't matter" | Internal tools get compromised. Attackers target the weakest link. |
| "We'll add security later" | Security retrofitting is 10x harder than building it in. Add it now. |
| "No one would try to exploit this" | Automated scanners will find it. Security by obscurity is not security. |
| "The framework handles security" | Frameworks provide tools, not guarantees. You still need to use them correctly. |
| "It's just a prototype" | Prototypes become production. Security habits from day one. |
| "Threat modeling is overkill here" | Five minutes of "how would I attack this?" prevents the design flaws no control can patch later. |
| "It's just LLM output, it's only text" | That "text" can be a SQL statement, a script tag, or a shell command. Treat it like any untrusted input. |

## Red Flags

- User input passed directly to database queries, shell commands, or HTML rendering
- Secrets in source code or commit history
- API endpoints without authentication or authorization checks
- Missing CORS configuration or wildcard (`*`) origins
- No rate limiting on authentication endpoints
- Stack traces or internal errors exposed to users
- Dependencies with known critical vulnerabilities
- Server fetches user-supplied URLs without an allowlist (SSRF)
- LLM/model output passed into a query, the DOM, a shell, or `eval`
- Secrets, PII, or the full system prompt placed inside an LLM context window

## Verification

After implementing security-relevant code:

- [ ] `npm audit` shows no critical or high vulnerabilities
- [ ] No secrets in source code or git history
- [ ] All user input validated at system boundaries
- [ ] Authentication and authorization checked on every protected endpoint
- [ ] Security headers present in response (check with browser DevTools)
- [ ] Error responses don't expose internal details
- [ ] Rate limiting active on auth endpoints
- [ ] Server-side URL fetches validated against an allowlist (no SSRF)
- [ ] LLM/model output validated and encoded before use (if AI features present)