A custom data converter is application-side logic that transforms workflow inputs and outputs before they are stored or retrieved by an orchestration system. In this pattern, the converter can encrypt and decrypt payloads transparently, letting the workflow engine process data without seeing the underlying sensitive content.
What Custom Data Converter Means in Workflow Orchestration
A custom data converter is application-side logic that transforms workflow inputs and outputs before they are persisted or read by an orchestration engine. It often makes sensitive payloads usable by the workflow platform without exposing the cleartext to the engine itself.
How Custom Data Conversion Works
The converter sits at the boundary between workflow code and the orchestration system’s storage layer. On write, it serializes or encrypts values before persistence; on read, it reverses that process so the application receives usable data again. This pattern is designed to keep the engine focused on scheduling and state management while the application controls how payloads are represented.
Because the converter is application-owned logic, its behavior becomes part of the trust boundary. The orchestration system may still handle metadata, routing, or history records, but the converter determines what the platform can actually see in stored payloads.
Why Teams Use It
The main use case is protecting workflow data that would otherwise be stored in a readable form by the orchestration layer. That can help with confidentiality, tenant separation, and selective disclosure when workflows must carry secrets, customer data, or regulated information through long-lived execution state.
It can also support portability. If the application owns the transformation logic, teams can change encryption schemes, payload formats, or serialization rules without depending on engine-level features that may vary across deployments. The trade-off is that the application now owns compatibility, key handling, and failure recovery for that data path.
Security and Operational Boundaries
A custom data converter does not make the workflow system itself trustworthy by default. It only changes what the engine receives and stores, so any compromise of the converter code, its configuration, or its keys can expose the same payloads it was meant to protect. The strongest protection comes when conversion logic, secret handling, and access to decrypted data are tightly scoped.
It also changes observability. Once payloads are encrypted or opaque, operators may lose visibility into stored content for debugging, audit, or search unless they design alternative controls for logs, metadata, and recovery procedures. That is often the right trade-off, but it should be deliberate rather than accidental.
Risk and Threat Considerations
Custom data converters create a concentrated trust point because they sit between application data and durable workflow storage. If the converter is weakly implemented, misconfigured, or paired with poor key management, attackers or insiders may target that boundary to recover payloads, tamper with stored state, or bypass intended confidentiality.
Failure mechanism: A failure usually appears when the converter leaks cleartext, reuses weak secrets, mishandles serialization, or decrypts data in a context that is broader than the workflow really needs.
Impact: The result can be exposure of sensitive workflow inputs or outputs, corrupted execution state, broken recoverability, and loss of trust in the orchestration layer’s handling of protected data.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST SP 800-53 Rev 5 sets the technical controls, while ISO/IEC 27001:2022 defines the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST SP 800-53 Rev 5 | IA-9 — Service Identification and Authentication | Covers authenticated handling of service-side workflow data transformations. |
| SC-12 — Cryptographic Key Establishment and Management | Applies when the converter encrypts or decrypts payloads using managed keys. | |
| SC-28 — Protection of Information at Rest | Directly supports protecting persisted workflow payloads through opaque or encrypted storage. | |
| Recommendation — Require authenticated service-to-service handling for any converter that processes protected payloads. Manage encryption keys separately from the converter and enforce controlled rotation and storage. Encrypt persisted workflow payloads so the orchestration engine stores protected data at rest. | ||
| ISO/IEC 27001:2022 | A.8.24 — Use of cryptography | Applies when the converter uses encryption to protect workflow payload confidentiality. |
| Recommendation — Apply approved cryptographic controls to payloads transformed by the custom converter. | ||
Practitioner Guidance
What to watch for: Treat the converter as security-sensitive application code, not as a formatting helper. The main governance question is who owns the transformation logic, who can change it, and how decrypted data is constrained once it leaves the storage boundary.
Practitioner takeaway: If the converter protects sensitive workflow state, test it like a security control, because its failures are often data exposure failures rather than ordinary application bugs.
Related resources from NHI Mgmt Group
- How should security teams govern custom foundation model training on proprietary data?
- How should security teams detect custom sensitive data without relying on regex?
- What breaks when a data loss prevention programme lacks accurate detection and custom policies?
- How should security teams implement DLP for Jira when projects contain sensitive data in issues, comments, attachments, and custom fields?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 26, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
