Search Open Technical Databases

Search Open Technical Databases [T1596]

Information

• Name: Search Open Technical Databases

• ID: T1596

• Tactics: TA0043

• Sub-Technique: T1596.003, T1596.002, T1596.001, T1596.004, T1596.005

Introduction

"Search Open Technical Databases" is a reconnaissance technique categorized under the MITRE ATT&CK framework (ID: T1596). Attackers leverage publicly available technical databases and repositories to gather sensitive technical information about targeted organizations. These databases can include code repositories, configuration files, technical forums, cloud storage buckets, and other publicly accessible resources. The information gathered can aid adversaries in planning further attacks, identifying vulnerabilities, or understanding the technical landscape of their targets.

Deep Dive Into Technique

Attackers utilizing this technique typically perform extensive searches across various publicly accessible technical databases and repositories. These databases include, but are not limited to:

• Code Repositories:

  • GitHub, GitLab, Bitbucket, SourceForge

  • Attackers search for leaked credentials, API keys, access tokens, passwords, or sensitive configuration files inadvertently committed to public repositories.

• Cloud Storage Services:

  • Amazon S3 buckets, Azure Blob Storage, Google Cloud Storage

  • Misconfigured buckets or publicly exposed storage services often contain sensitive data such as backups, code, or personal information.

• Technical Forums and Q&A Platforms:

  • Stack Overflow, Stack Exchange, Reddit, Pastebin

  • Employees may unintentionally disclose sensitive technical details or configurations when seeking assistance or troubleshooting.

• Publicly Accessible Databases and Indices:

  • Shodan, ZoomEye, Censys, BinaryEdge

  • These platforms index internet-connected devices and services, exposing details about open ports, running services, software versions, and vulnerabilities.

• Search Engines and Web Archives:

  • Google, Bing, Internet Archive (Wayback Machine), and specialized search engines (Google Dorks)

  • Attackers frequently use advanced search operators (Google Dorking) to uncover sensitive documents, configuration files, or exposed administrative interfaces.

Real-world procedures often involve automated scripts, bots, or specialized tools designed to efficiently scrape, search, and analyze large datasets. Attackers may also leverage APIs provided by these platforms to automate the reconnaissance process.

When this Technique is Usually Used

This technique is primarily utilized during the reconnaissance and initial access phases of the cyber attack lifecycle. Common scenarios include:

• Initial Reconnaissance:

  • Attackers gather information to map out an organization's technical landscape, infrastructure, and potential vulnerabilities.

• Credential Harvesting:

  • Searching code repositories and forums for leaked credentials, API keys, or sensitive configuration information that can facilitate unauthorized access.

• Vulnerability Identification:

  • Attackers search databases such as Shodan or ZoomEye to discover exposed services, open ports, outdated software versions, or misconfigured systems.

• Supply Chain Attacks:

  • Gathering technical intelligence on third-party vendors and suppliers to identify weak points in the supply chain.

• Pre-Attack Intelligence Gathering:

  • Collecting technical details to prepare targeted phishing campaigns, exploit development, or social engineering attacks.

How this Technique is Usually Detected

Detection of this reconnaissance activity can be challenging, as attackers leverage publicly available resources and databases. However, organizations can implement specific measures and tools to detect and monitor these activities:

• Monitoring Public Code Repositories:

  • Tools such as GitGuardian, Git-secrets, TruffleHog, or Gitrob can detect leaked credentials or sensitive data committed to public repositories.

• Cloud Storage Monitoring:

  • Regular audits and monitoring tools (e.g., AWS Config, Azure Security Center, Google Cloud Security Command Center) can detect misconfigured buckets or storage services.

• Threat Intelligence Platforms:

  • Platforms such as Recorded Future, Digital Shadows, or RiskIQ monitor dark web forums, paste sites, and technical forums for leaked credentials or sensitive data.

• Web Application Firewalls (WAFs) and IDS/IPS:

  • Monitoring unusual traffic patterns, repeated scans from known scanning IP addresses, or suspicious user-agent strings.

• Log Analysis and SIEM Solutions:

  • Analyzing logs for unusual access patterns, repeated failed authentication attempts, or access attempts from external IP addresses known to be associated with reconnaissance tools.

Indicators of Compromise (IoCs) related to this technique typically include:

• Sudden spikes in traffic from known reconnaissance services (Shodan, Censys, ZoomEye).

• Detection of leaked credentials or sensitive data in public repositories.

• Alerts from monitoring tools about publicly exposed cloud storage services.

• Suspicious queries or searches originating from external IP addresses against publicly exposed services.

Why it is Important to Detect This Technique

Early detection of the "Search Open Technical Databases" technique is crucial due to the significant impacts it can lead to:

• Credential Exposure:

  • Leaked credentials, API keys, or tokens can enable attackers to gain unauthorized access to critical systems, databases, or cloud services.

• Data Breaches and Information Leakage:

  • Sensitive information discovered in publicly accessible databases can lead to data breaches, intellectual property theft, or regulatory compliance violations.

• Facilitation of Targeted Attacks:

  • Technical intelligence gathered during reconnaissance can be used to tailor and execute sophisticated phishing attacks, social engineering campaigns, or exploit development.

• Infrastructure Compromise:

  • Attackers can exploit identified vulnerabilities, misconfigurations, or exposed services to compromise organizational infrastructure, leading to service disruptions or unauthorized access.

• Reputational Damage and Financial Loss:

  • Successful exploitation based on reconnaissance data can result in significant financial losses, regulatory fines, and long-term reputational damage.

Early detection enables organizations to proactively remediate exposed data, strengthen security configurations, and reduce the overall attack surface, significantly reducing potential damage and impact.

Examples

Real-world examples demonstrating "Search Open Technical Databases" include:

• Uber GitHub Credential Leak (2016):

  • Attack Scenario:

    • Attackers discovered AWS credentials publicly committed to Uber’s GitHub repositories.

  • Tools and Methods:

    • GitHub search, automated scanning tools (e.g., Gitrob, TruffleHog).

  • Impact:

    • Attackers gained unauthorized access to Uber’s AWS infrastructure, resulting in the exposure of personal data of approximately 57 million customers and drivers.

• Capital One AWS S3 Misconfiguration (2019):

  • Attack Scenario:

    • Attackers identified misconfigured AWS S3 buckets through publicly accessible indexing services.

  • Tools and Methods:

    • Cloud storage scanning tools, Shodan, custom scripts.

  • Impact:

    • Exposure of personal and financial data of over 100 million customers, resulting in significant regulatory fines and reputational damage.

• SolarWinds Supply Chain Attack (2020):

  • Attack Scenario:

    • Attackers performed extensive reconnaissance on technical databases and forums to understand SolarWinds’ build and deployment processes.

  • Tools and Methods:

    • Technical forums, public documentation, code repositories, and cloud storage services.

  • Impact:

    • Compromise of SolarWinds Orion software updates, leading to cyber espionage campaigns impacting numerous government agencies and private organizations.

• Shodan-Assisted IoT Device Attacks:

  • Attack Scenario:

    • Attackers use Shodan to identify internet-exposed IoT devices with default credentials or known vulnerabilities.

  • Tools and Methods:

    • Shodan, ZoomEye, Censys, automated scanning and exploitation scripts.

  • Impact:

    • Compromise of IoT devices, formation of botnets (e.g., Mirai), and subsequent Distributed Denial-of-Service (DDoS) attacks.

• Pastebin Credential Dumps:

  • Attack Scenario:

    • Attackers regularly monitor Pastebin and similar platforms for leaked credentials or sensitive information.

  • Tools and Methods:

    • Automated scraping tools, scripts, and threat intelligence feeds.

  • Impact:

    • Unauthorized access to corporate systems, email accounts, or cloud infrastructure, leading to data breaches and financial losses.

These examples highlight the critical importance of proactively monitoring and securing publicly accessible technical databases, repositories, and resources to prevent unauthorized reconnaissance and subsequent cyber attacks.