Injection Flaws in Rails with Mongodb

Injection flaws in a Rails application using MongoDB typically arise when untrusted input is incorporated into database queries without proper sanitization or type validation. Unlike SQL, MongoDB queries are expressed as JSON-like documents, and Ruby code often builds these documents by interpolating user-controlled values directly into hashes. This pattern can lead to query injection where an attacker influences the structure or content of the query.

Consider a typical controller that looks up a user by a string parameter:

# Unsafe: direct interpolation into a MongoDB selector
user = User.where(email: params[:email]).first

If the application builds a more complex filter by merging user input into a hash, the risk increases:

# Unsafe: merging raw params into a selector
selector = { status: params[:status] }
User.where(selector).each { |u| puts u.name }

In MongoDB for Rails (via the mongoid gem), field names and values are both dynamic, which can inadvertently allow an attacker to inject operators. For example, if the application uses string keys derived from user input, an attacker might supply { "$ne" => "" } as a value expecting it to be treated as a literal string, but MongoDB interprets it as an operator that matches documents where the field is not equal to the provided value.

Another scenario involves sort parameters. If sorting is driven by user input without strict allowlisting, an attacker can inject operator-like structures that alter query behavior:

# Unsafe: unsorted input used directly
User.order(params[:sort_by])

Because operators in MongoDB begin with a dollar sign (e.g., $gt, $in), failing to validate or escape input allows unintended query logic. This can lead to information disclosure, such as bypassing intended filters or extracting data across privilege boundaries.

LLM/AI Security considerations also intersect here: if an API endpoint uses model-generated prompts that include raw user input later stored or logged, injection risks can extend beyond the database into prompt leakage or injection into model instructions. middleBrick’s LLM/AI Security checks specifically test for system prompt leakage and output exposure of sensitive data like API keys or PII that might be inadvertently surfaced through injected query results.

middleBrick scans an unauthenticated attack surface in 5–15 seconds and can surface these classes of issues among its 12 parallel security checks, providing prioritized findings with severity and remediation guidance. For teams using the CLI, running middlebrick scan <url> can quickly surface such risks without agents or credentials.

To mitigate injection flaws with MongoDB in Rails, prefer whitelisting, strict type validation, and safe query construction. Avoid merging raw params directly into selectors, and treat all user input as untrusted.

1) Use strong parameter filtering and type casting

Always use Rails strong parameters and cast to expected types before building queries:

def user_params
  params.require(:user).permit(:email, :status, :sort_by)
end

# Cast and validate before querying
email = user_params[:email].to_s.strip
status = user_params[:status].to_s
sort_by = user_params[:sort_by].to_s

2) Avoid operator injection by using explicit field names and values

Do not allow raw user input to become document keys or operator names. Instead, map inputs to known fields:

allowed_statuses = %w[active archived suspended]
status = user_params[:status]
status = allowed_statuses.include?(status) ? status : nil

selector = {}
selector[:status] = status if status.present?
User.where(selector).each { |u| puts u.name }

3) Validate sort parameters against an allowlist

Never pass raw input to order clauses. Use a mapping to ensure only safe fields and directions are used:

ALLOWED_SORTS = { 'name' => 'name ASC', 'created_at' => 'created_at DESC' }
sort_key = ALLOWED_SORTS[user_params[:sort_by]]
User.order(sort_key || 'created_at DESC')

4) Use MongoDB’s built-in escaping for dynamic fields when necessary

If dynamic field names are required (rare), ensure they are validated and sanitized to prevent injection of operators:

field = user_params[:field_name].to_s
if field.match?(/\\(?!\$)/) || %w[$gt $lt $in $ne $or].include?(field)
  # Reject or sanitize dangerous field names
  raise ArgumentError, 'Invalid field name'
end

# Use string-based key construction carefully
User.where(field => user_params[:value])

5) Prefer criteria-style chaining over raw hash merging

Chain where clauses rather than merging hashes that may contain user input:

relation = User.all
relation = relation.where(status: user_params[:status]) if user_params[:status].present?
relation = relation.where(email: user_params[:email]) if user_params[:email].present?
relation.each { |u| puts u.name }

For teams using the Web Dashboard, scan endpoints with the middleBrick dashboard to track security scores and findings over time. The Pro plan adds continuous monitoring and can integrate GitHub Actions to fail builds if risk scores drop below a chosen threshold. The MCP Server allows AI coding assistants to trigger scans directly from the editor, helping catch unsafe patterns before code is committed.