Inferensys

Glossary

Cross-Domain Solution (CDS)

A security appliance that provides the ability to manually or automatically access or transfer information between two or more differing security domains, enforcing strict data inspection and filtering.
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SECURITY ARCHITECTURE

What is Cross-Domain Solution (CDS)?

A Cross-Domain Solution (CDS) is a specialized security appliance that enables controlled information transfer between two or more distinct security domains, enforcing strict data inspection, filtering, and policy enforcement to prevent unauthorized leakage.

A Cross-Domain Solution (CDS) is a hardware and software security appliance that provides the ability to manually or automatically access or transfer information between two or more differing security domains. It acts as a guarded gateway, enforcing mandatory access control (MAC) policies and performing deep content inspection to ensure that only explicitly authorized data crosses the boundary between networks operating at different classification levels.

Unlike a simple firewall, a CDS performs protocol break and data sanitization, terminating the connection on one side, inspecting the payload for malware or hidden metadata, and regenerating a clean transaction on the other side. This ensures no direct network path exists between domains, preventing protocol-level attacks and enforcing a strict data diode or bidirectional guard function based on the system's accreditation.

GUARDING THE GAP

Core Characteristics of a CDS

A Cross-Domain Solution is not a simple firewall; it is a specialized security appliance that enforces a structured, inspectable bridge between networks of differing classification levels.

01

Mandatory Access Control Enforcement

A CDS enforces Mandatory Access Control (MAC) policies, not discretionary ones. It makes an authoritative decision based on security labels (e.g., Top Secret, Secret, Unclassified) attached to both subjects (users) and objects (data). This ensures data transfers comply with a formal security model, typically Bell-LaPadula (no read up, no write down) or Biba (integrity-focused), preventing unauthorized downgrades or leaks.

02

Deep Content Inspection & Sanitization

Unlike a network firewall that inspects packet headers, a CDS performs full-stack, deep content inspection. It deconstructs files and message formats to validate data integrity and eliminate threats:

  • Format Validation: Verifies a file's magic bytes match its extension to prevent masquerading attacks.
  • Active Content Stripping: Removes embedded macros, JavaScript, and zero-width characters that could harbor steganographic data.
  • Schema Validation: Checks structured data against a strict, pre-approved schema, discarding any malformed or extraneous fields.
03

Unidirectional & Bidirectional Flows

CDS architectures are defined by their data flow topology. A Unidirectional Gateway (often hardware-enforced via a data diode) physically guarantees data can only travel from a low to a high domain, making exfiltration impossible. A Bidirectional CDS allows controlled two-way communication but requires two independent, logically separated inspection paths—one for each direction—each enforcing its own distinct security policy to prevent a bypass.

04

Session Termination & Protocol Break

A fundamental principle is the complete break of the OSI protocol stack. The CDS terminates the TCP session from the source network at the application layer, extracts the payload, and initiates a brand-new session to the destination. This prevents blind tunneling attacks where malicious Layer 2/3 traffic is encapsulated within an allowed protocol. The source and destination networks never share a direct link-layer connection.

05

Tamper-Proof Auditing

Every byte crossing the boundary generates a cryptographically signed audit record. The CDS logs the source IP, destination IP, user identity, file hash, security labels, and the full sanitized payload. These logs are typically streamed to a dedicated, immutable audit server in the high-security domain to provide non-repudiation and support forensic analysis in the event of a spillage investigation.

06

Human Review & Automated Release

CDS deployments support two operational modes. Automated Release allows data that passes all automated checks to cross instantly, essential for real-time sensor data. Manual Review (or 'High Assurance Guard' mode) places flagged or high-risk transfers into a quarantine queue. A trusted human analyst must visually inspect the sanitized content and explicitly approve the release, providing a final cognitive check against complex data correlation attacks.

CROSS-DOMAIN SOLUTIONS

Frequently Asked Questions

Clear, technically precise answers to the most common questions about the architecture, security mechanisms, and operational constraints of Cross-Domain Solutions.

A Cross-Domain Solution (CDS) is a specialized security appliance that provides the ability to manually or automatically access or transfer information between two or more differing security domains, enforcing strict data inspection and filtering. It operates as a controlled interface, typically sitting between a low-security network and a high-security enclave. The core mechanism involves deep packet inspection, protocol break, and content disarm and reconstruction (CDR). Instead of simply routing packets, a CDS terminates the connection on the low side, validates the data against a mandatory access control policy, strips active content like macros and scripts, and rebuilds a sanitized version of the data before establishing a new connection on the high side. This protocol break ensures that no network-layer attacks can traverse the boundary, as the original session is destroyed and a new, clean session is initiated. Hardware-enforced data diodes are often integrated to physically guarantee unidirectional flow when bidirectional communication is not required, making reverse channel exploitation physically impossible.

Prasad Kumkar

About the author

Prasad Kumkar

CEO & MD, Inference Systems

Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.

His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.