How to Audit NoSQL for Security Vulnerabilities?

Wondering how to find the cracks in your MongoDB, Redis, Cassandra or Couchbase databases before the bad guys do? As your personal cybersecurity guide, I‘ll share proven methods to rigorously audit non-SQL database security, identify hidden risks, and fix them like experts.

Content Navigation show

By spending just an hour inspecting your NoSQL deployment using specialized tools we‘ll cover, you‘ll plug security anti-patterns that leave data exposed. Follow this geek-approved game plan to reinforce database safeguards through audits before embarrassment or regulatory penalties hit.

We‘ll walk step-by-step how to:

  • Use popular tools to automatically detect misconfigurations
  • Interpret & prioritize risks uncovered for remediation
  • Apply database-specific hardening techniques
  • Configure native encryption correctly
  • When to call in specialized human testers

And more to rigorously secure NoSQL clusters holding precious data as their widespread adoption introduces new threats.

NoSQL Security Risks Proliferate

First, context on growing danger as NoSQL databases become lucrative targets based on surging popularity – over 75% of new applications rely on non-relational databases for their flexibility and horizontal scale.

Damage From Recent NoSQL Breaches:

  • 53 million leaked NoSQL records in 2021 3x SQL leaks
  • Average breach impact $4.35 million, lasting 279 days
  • 80% not secure default configurations prior to incidents

Yet few understand NoSQL-specific vulnerabilities compared to traditional SQL RDBMS hardened over decades. Direct file access, unofficial APIs and immature access controls impose new risk paradigms.

This guide arms you to beat hackers exploiting these attack surfaces through rigorous self-audits. Let‘s level set on the pressing dangers needing vigilance as NoSQL adoption accelerates while security practices scramble to catch up.

Common NoSQL Vulnerability Classes

While avoiding SQL injection, NoSQL flexibility introduces fresh weakness types if not hardened properly.

Injection Attacks
Unique query languages allow alternate injection channels like directly inserting database commands, unlike SQL syntax.

Access Control Issues
Unprotected instances, open authentication and ambiguous permissions grant excessive powers.

Data Exposure
On-disk storage and transfer often lacks encryption for security and performance.

Insecure Interfaces
Unofficially supported client libraries, administrative consoles and debug APIs bypass controls.

Account Misuse
Hardcoded, shared and overly privileged credentials spawn insider threats.

Insufficient Logging
Missing activity trails allow intrusions to go undetected for months.

We will focus our auditing lens on common leaks through these NoSQL-specific risk areas next using purpose-built tools.

Scanning for Configuration Issues with NoSQLMap

NoSQLMap is an open-source Python scanner tailor-made to catch security missteps specific to non-relational databases. By combining configuration checks with injection probes, it uncovers problems otherwise missed.

Available detection modules cover popular options:

  • MongoDB
  • Cassandra
  • Redis
  • CouchDB
  • Elasticsearch
  • HBase

I suggest installing NoSQLMap even if not yet using NoSQL because future migration from legacy systems is inevitable for most. Get ahead of change by already understanding unique security nuances.

Installing & Running NoSQLMap

NoSQLMap depends on Python and the setuptools package. Install them before running:

pip install pymongo urllib argparse
git clone https://github.com/codingo/NoSQLMap.git 
cd NoSQLMap 
python setup.py install

Next execute python nosqlmap.py and select your target database type. You will be prompted for scan options – use the IP and port your NoSQL instance is listening on: 

Select MongoDB scan options:

Host: 65.2.1.100
Port: 27017 
. . .

That‘s it! NoSQLMap will audit for dozens of security anti-patterns and misconfigurations flagged as critical, high, medium or low risk.

Here‘s a sample summary report:

Critical Risk Vulnerabilities [2]
------------------------------
+ Authentication enabled: No 
+ Run against production: Yes

High Risk Vulnerabilities [4]
-----------------------------
. . .

Medium Risk Vulnerabilities [8]  
-------------------------------- 
. . .

Low Risk Vulnerabilities [3]
----------------------------
. . . 

Finished scanning in 2 minutes 37 seconds
17 total vulnerabilities reported

This outlines clear issues for prioritized mitigation before trouble strikes. Having an automated baseline audit establishes solid security hygiene quickly around your NoSQL deployment.

Customizing NoSQLMap

NoSQLMap offers advanced features like debug modes, using proxy connections and DNS cache poisoning for temporary access. The project repository has examples for integrating into automated pipelines.

As an open-source Python project, you can also tweak modules or add checks suited to your unique stack. For common NoSQL databases, NoSQLMap delivers an invaluable free security audit.

However, its code-based model also means staying updated as new issues emerge requires some effort. For maximum set-and-forget assurance, we‘ll cover managed scanning services next.

ScoutSuite – Scans as a Service

Migrating security tools into cloud-based services lowers operational overhead for users by handling underlying framework updates automatically. ScoutSuite by NCCGroup provides continuous visibility into misconfigurations across major cloud providers via a SaaS model.

Although not focused specifically on NoSQL, ScoutSuite supports detecting issues like:

  • Unprotected database instances
  • Open security groups
  • Encryption absent
  • Suspicious IAM roles

Pricing starts at $18 monthly per AWS account scanned. A free trial lets you evaluate risk levels before committing spend.

When to Engage Professional Penetration Testing

However adept at catching bad configurations, automated tools have blindspots detecting logical vulnerabilities requiring human insight.

For NoSQL deployments handling sensitive data or mission-critical apps, supplementing self-audits with professional penetration testing is wise for greatest risk coverage despite higher cost.

A typical commercial pentest engagement includes:

  • Infrastructure and data flow mapping
  • Attempted authentication bypass
  • Testing encryption controls
  • Reverse engineering clients
  • Raw database access tricks

Look for firms that detail NoSQL penetration testing methodology in their service briefs for best results.

Their detailed exit report identifies missed issues and recommends fixes with prioritized remediation roadmaps. While expensive around $150 per hour, can prove well worth preventing high-impact data disasters.

Implementing Audit Recommendations

While essential for awareness, audits themselves do not secure databases – concrete fix implementation does. Use risk ranked findings to methodically harden vulnerabilities:

Activate Authentication

  • Require credentials by disabling anonymous access
  • Install a secure password vault to avoid hardcoded secrets

Limit Network Exposure

  • Place databases inside private VPCs instead of public cloud
  • Restrict IP ranges allowed to connect

Apply Database Hardening:

  • Follow vendor security checklists like MongoDB domain hardening
  • Continuously apply latest patched releases

Enforce Encryption

  • Activate TLS/SSL for all client connections
  • Enable at-rest transparency or field encryption

Centralize Activity Logging

  • Forward audit logs to cloud-scale tooling for analysis
  • Retain historical logs to detect slow-burn intrusions

These areas provide 60%+ risk reduction for typical insecure configurations. Now let‘s examine their real-world impact through an example company‘s evolving NoSQL security journey.

Case Study: Securing MongoDB In Phases

Consider a hypothetical startup GeoSearch building location-based mobile apps powered by MongoDB behind the scenes. Early on, developer experience was prioritized over security in MongoDB set up:

Phase 1 – Ignorance is Risk: MVP Deployment

GeoSearch wanted to test their app with users quickly during development. In this phase:

  • MongoDB deployed on publicly accessible cloud VM
  • Anonymous authentication permitted
  • Developer credentials shared in GitHub
  • Network left completely open

This allowed easy experimentation to validate app concepts. However, it also exposed sensitive personal data to facile unauthorized access without realizing it.

Phase 2 – Security Incident: Breach Detecton

Months later, GeoSearch was informed their unprotected MongoDB instance was breached by hackers who leaked user profiles and messages online. Forensic security auditors confirmed:

  • No authentication enabled on MongoDB
  • No network controls restricting access
  • Plaintext data with no encryption applied

This highlighted gaping lack of access controls. Thankfully impact was minimized during early testing phases without widespread adoption. The leaked incident triggered priority investment into security.

Phase 3: Vulnerability Remediation

GeoSearch methodically hardened MongoDB in phases after the incident before further launch:

Short term

  • Upgraded MongoDB to enable access control lists
  • Restricted network route access using VPC constructs
  • Mandated SSL/TLS traffic encryption

Medium Term

  • Tested field-level encryption for sensitive PII data
  • Instituted IAM policies restricting DB permissions
  • Setup hardened bastion servers as sole access gateways

Longer Term

  • Centralized logging and monitoring for all DB interactions
  • Recurrent penetration testing to catch missed flaws
  • Ongoing configuration management as code

A combination of competency gain and modern security tooling inoculated GeoSearch as applications scaled, preventing repeats of early ignorant exposures.

Let Audits Guide Your NoSQL Security Maturity

Like GeoSearch‘s journey illustrates, auditing and securing NoSQL databases is an iterative path as teams balance risk and functionality. Avoid brandedheadline disasters by:

  • Leveraging automated scans frequently to catch drift
  • Obtaining periodic pentesting even if just annually
  • Building security ops skills to own controls instead of depending on vendors

This scalable model will serve your data stores‘ protection beyond early phases as adoption spreads enterprise-wide.

In closing, constantly evolving technology like NoSQL will always introduce novel attacks – vigilant auditing uncovers them early before disaster strikes if leveraged routinely to challenge security assumptions as configurations and apps change.

Book regular audits now before unwanted front page coverage forces reactive attention. Our guide outlined optimal tools for preventative audits allowing smarter database architecture keeping your company out of the headlines!

Tags: