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Threat Model Analysis for robb/cartography

Threat: Malicious Cartography Configuration

  • Threat: Malicious Cartography Configuration

    • Description: An attacker modifies Cartography's configuration files (e.g., config.yaml, environment variables) to point it to a malicious Neo4j instance controlled by the attacker, or to alter synchronization parameters in a way that compromises data integrity or security. This could be achieved through compromised server access where Cartography is running, exploiting vulnerabilities in the Cartography deployment process, or social engineering to trick an administrator into making harmful configuration changes.
    • Impact:
      • Data Poisoning: The attacker's malicious Neo4j instance can inject false data into Cartography, leading to incorrect security assessments and potentially causing automated security tools to make incorrect decisions.
      • Data Exfiltration: Cartography could unknowingly send sensitive infrastructure data to the attacker's database, resulting in a data breach.
      • Denial of Service: The malicious database could be configured to be unresponsive, preventing Cartography from functioning and disrupting security monitoring.
    • Affected Component: Cartography's configuration files (e.g., config.yaml), environment variables, and the cartography.config module.
    • Risk Severity: High
    • Mitigation Strategies:
      • File System Permissions: Strictly restrict access to Cartography's configuration files to only authorized users and processes. Use the principle of least privilege.
      • Configuration Management: Use configuration management tools (Ansible, Chef, Puppet, etc.) to manage Cartography's configuration and detect unauthorized changes. This ensures consistency and makes unauthorized modifications easily detectable.
      • Integrity Checks: Implement integrity checks (e.g., checksums, file integrity monitoring) on configuration files to detect tampering.
      • Input Validation: Validate any user-provided input that influences Cartography's configuration (e.g., environment variables) to prevent injection of malicious values.
      • Regular Audits: Periodically review Cartography's configuration for any anomalies or deviations from the expected settings.

Threat: Insecure Deserialization in Cartography Modules

  • Threat: Insecure Deserialization in Cartography Modules

    • Description: Cartography, or one of its Intel modules, uses insecure deserialization of data received from cloud providers or other external sources. An attacker could craft malicious input that, when deserialized, executes arbitrary code on the Cartography server. This is particularly relevant if Cartography uses Python's pickle module or similar libraries (like yaml.unsafe_load) without proper validation. The attacker would need to find a way to inject this malicious input, potentially through a compromised cloud provider API or a man-in-the-middle attack.
    • Impact:
      • Remote Code Execution (RCE): The attacker gains complete control over the Cartography server, allowing them to execute arbitrary commands.
      • Data Breach: The attacker can access and exfiltrate sensitive data stored on the server or accessible from the server, including cloud provider credentials and infrastructure data.
      • System Compromise: The attacker can use the compromised server to launch further attacks against other systems in the network.
    • Affected Component: Cartography's Intel modules (e.g., cartography.intel.aws, cartography.intel.gcp, cartography.intel.azure), any module that uses deserialization libraries (e.g., pickle, yaml.unsafe_load).
    • Risk Severity: Critical
    • Mitigation Strategies:
      • Avoid Insecure Deserialization: Avoid using insecure deserialization libraries like pickle unless absolutely necessary and with extreme caution.
      • Input Validation: If deserialization is required, rigorously validate the input data before deserializing it. Use a schema validation library or a safe deserialization library (e.g., json for JSON data, yaml.safe_load for YAML data). Never deserialize data from untrusted sources.
      • Principle of Least Privilege: Run Cartography with the least privilege necessary on the host system. This limits the damage an attacker can do if they achieve code execution.
      • Regular Security Audits: Conduct regular security audits of Cartography's code, focusing specifically on data handling and deserialization practices.
      • Dependency Management: Keep all dependencies, including those used by Intel modules, up-to-date to patch any known vulnerabilities in deserialization libraries.

Threat: Privilege Escalation via Cartography Vulnerabilities

  • Threat: Privilege Escalation via Cartography Vulnerabilities

    • Description: An attacker exploits a vulnerability within Cartography's own code (not Neo4j or the OS) to gain higher privileges than initially granted. This could be a bug in how Cartography handles permissions, interacts with the operating system, or manages its own internal state. The attacker would likely need some initial access to the system running Cartography, even with limited privileges.
    • Impact:
      • Increased Access: The attacker gains broader access to the system running Cartography, potentially including administrative privileges.
      • Data Compromise: The attacker can access, modify, or delete more data, including Cartography's configuration and potentially sensitive information it has collected.
      • System Control: The attacker may be able to control the Cartography service itself, altering its behavior or shutting it down.
    • Affected Component: Cartography application code (various modules, depending on the specific vulnerability).
    • Risk Severity: High
    • Mitigation Strategies:
      • Regular Updates: Keep Cartography updated to the latest version to patch any known security vulnerabilities in its codebase.
      • Least Privilege: Run Cartography with the least privilege necessary on the host system. This limits the impact of a successful privilege escalation.
      • Code Review: Conduct thorough code reviews of Cartography's source code, focusing on security-sensitive areas like permission handling and system interactions.
      • Vulnerability Scanning: Regularly scan Cartography's code for vulnerabilities using static analysis tools.
      • Penetration Testing: Conduct penetration testing specifically targeting Cartography to identify and address any privilege escalation vulnerabilities.