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/sast-sqli

Detect SQL injection vulnerabilities in a codebase using a three-phase approach: recon (find unsafe SQL construction sites), batched verify (trace user input to those sites in parallel subagents, 3 sites each), and merge (consolidate batch results). Covers string concat,

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sast-skills
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$ npx -y skills add utkusen/sast-skills --skill sast-sqli --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/sast-sqli

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Detect SQL injection vulnerabilities in a codebase using a three-phase approach: recon (find unsafe SQL construction sites), batched verify (trace user input to those sites in parallel subagents, 3 sites each), and merge (consolidate batch results). Covers string concat,

SKILL.md

sast-sqli.SKILL.md
name: sast-sqli
description: >-
  Detect SQL injection vulnerabilities in a codebase using a three-phase approach:
  recon (find unsafe SQL construction sites), batched verify (trace user input to
  those sites in parallel subagents, 3 sites each), and merge (consolidate batch
  results). Covers string concat, f-strings, unsafe ORM methods, and dynamic
  identifiers. Requires sast/architecture.md (run sast-analysis first). Outputs
  findings to sast/sqli-results.md. Use when asked to find SQLi or database
  injection bugs.

SQL Injection (SQLi) Detection

You are performing a focused security assessment to find SQL injection vulnerabilities in a codebase. This skill uses a three-phase approach with subagents: **recon** (find vulnerable SQL construction sites), **batched verify** (taint analysis in parallel batches of 3), and **merge** (consolidate batch reports into one file).

**Prerequisites**: `sast/architecture.md` must exist. Run the analysis skill first if it doesn't.

---

What is SQL Injection

SQL injection occurs when user-supplied input is incorporated into SQL queries through string concatenation or interpolation rather than parameterized binding. This allows attackers to alter query logic, bypass authentication, extract sensitive data, modify or delete records, and in some configurations execute OS commands.

The core pattern: *unvalidated, unparameterized user input reaches a SQL query execution call.*

What SQLi IS

  • Concatenating user input directly into a SQL string: `"SELECT * FROM users WHERE name = '" + username + "'"`
  • Using string formatting to build queries: `f"SELECT * FROM orders WHERE id = {order_id}"`
  • Dynamic `ORDER BY` / `GROUP BY` / table/column names from user input with no allowlist validation
  • ORM raw query methods with unsanitized input: `User.objects.raw(f"SELECT * WHERE id={id}")`, `$queryRawUnsafe(input)`
  • Second-order injection: input is stored in the DB and later used in a raw query without re-sanitization

What SQLi is NOT

Do not flag these as SQLi:

  • **IDOR**: Changing `?id=1` to `?id=2` to access another user's data — that's Insecure Direct Object Reference, a separate class
  • **Mass assignment**: Setting extra ORM model fields from user input — different vulnerability
  • **XSS via database**: Storing a `<script>` tag in the DB that's later rendered unescaped — that's XSS, not SQLi
  • **NoSQL injection**: Injecting into MongoDB operators — similar concept but a distinct vulnerability class
  • **Safe ORM queries**: Parameterized ORM lookups like `User.objects.filter(id=user_id)` or `User.find(params[:id])` — do not flag these

Patterns That Prevent SQLi

When you see these patterns, the code is likely **not vulnerable**:

**1. Parameterized queries / prepared statements (most common fix)**

# Python — cursor.execute with tuple binding
cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))

# Node.js — mysql2 / pg placeholder binding
db.query("SELECT * FROM users WHERE id = ?", [userId])
pool.query("SELECT * FROM users WHERE id = $1", [userId])

# Java — PreparedStatement
PreparedStatement ps = conn.prepareStatement("SELECT * FROM users WHERE id = ?");
ps.setInt(1, userId);

# Go — database/sql placeholder
db.QueryRow("SELECT * FROM users WHERE id = $1", userID)

# PHP — PDO with named params
$stmt = $pdo->prepare("SELECT * FROM users WHERE id = :id");
$stmt->execute(['id' => $userId]);

# C# — SqlCommand with parameters
cmd.CommandText = "SELECT * FROM users WHERE id = @id";
cmd.Parameters.AddWithValue("@id", userId);

**2. ORM query builder (safe by default)**

# Django ORM
User.objects.filter(id=user_id)

# ActiveRecord (Rails)
User.find(params[:id])
User.where(name: params[:name])

# Prisma (tagged template literal form of $queryRaw)
await prisma.$queryRaw`SELECT * FROM users WHERE id = ${userId}`

# Laravel Eloquent (non-raw)
User::find($id)

**3. Allowlist validation for dynamic identifiers**

# Dynamic ORDER BY — validate column name against a hardcoded set before interpolating
ALLOWED_COLUMNS = {'name', 'created_at', 'price'}
if sort_col not in ALLOWED_COLUMNS:
    raise ValueError("Invalid column")
query = f"SELECT * FROM products ORDER BY {sort_col}"  # safe only after allowlist check

---

Vulnerable vs. Secure Examples

Python — Django (raw SQL)

# VULNERABLE: f-string interpolation in raw()
def search_users(request):
    username = request.GET.get('username')
    users = User.objects.raw(f"SELECT * FROM auth_user WHERE username = '{username}'")
    return JsonResponse(list(users.values()), safe=False)

# SECURE: parameterized raw()
def search_users(request):
    username = request.GET.get('username')
    users = User.objects.raw("SELECT * FROM auth_user WHERE username = %s", [username])
    return JsonResponse(list(users.values()), safe=False)

Python — Flask / SQLAlchemy

# VULNERABLE: f-string into text()
@app.route('/search')
def search():
    name = request.args.get('name')
    result = db.session.execute(text(f"SELECT * FROM products WHERE name = '{name}'"))
    return jsonify(result.fetchall())

# SECURE: named bound parameter
@app.route('/search')
def search():
    name = request.args.get('name')
    result = db.session.execute(
        text("SELECT * FROM products WHERE name = :name"), {"name": name}
    )
    return jsonify(result.fetchall())

Python — sqlite3 / psycopg2

# VULNERABLE
def get_user(username):
    cursor.execute("SELECT * FROM users WHERE username = '" + username + "'")
    return cursor.fetchone()

# SECURE
def get_user(username):
    cursor.execute("SELECT * FROM users WHERE username = ?", (username,))
    return cursor.fetchone()

Node.js — mysql2

// VULNERABLE: template literal in query string
app.get('/user', async (req, res) => {
  const { id } = req.query;
  const [rows] = await db.query(`SELECT * FROM users WHERE id = ${id}`);
  res.json(rows);
});

// SECURE: placeholder
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Ships withsast-skills

A collection of agent skills that turn your LLM coding assistant into a fully functional SAST scanner to find vulnerabilities in your codebase. Works natively with Claude Code, Codex, Opencode, Cursor and any other assistant that supports agent skills.

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