Enterprise Discovery Architecture

1. What the architecture is for

Cryptographic discovery is an enterprise evidence problem. The objective is not merely to list algorithms or certificates, but to establish where cryptography is used, which systems and protocols use it, what data or services it protects, and how the findings relate to assets, identities, credentials, access paths, and business priorities. The cited quantum-readiness guidance specifically calls for identifying quantum-vulnerable algorithms in network protocols, end-user systems and servers, applications and libraries, firmware and software updates, and cryptographic code or dependencies in CI/CD pipelines. It also recommends correlating cryptographic inventory with asset, identity and access, endpoint, and continuous-diagnostics inventories.【】1

This makes the architecture broader than a vulnerability scanner. It must collect observations from different technical surfaces, reconcile them into comparable records, and retain enough context to support risk decisions. A preliminary NIST discovery architecture describes ingesting normalized platform output and producing a prioritization list, while noting that its proposed architecture was subject to change as experimentation and community feedback continued. That status matters: the design should distinguish established organizational requirements from provisional implementation choices.【】2

2. Scope collectors by evidence surface

Collectors should be scoped to the evidence available at each surface and should state what they can and cannot observe. Source and build collectors inspect repositories, dependency declarations, pipeline configuration, build logs, and cryptographic code or dependencies. CI/CD guidance describes pipelines that move source through building, testing, security scanning, packaging, deployment, and operations; it also distinguishes application code, application-services code, infrastructure as code, policy as code, and observability as code. These code types can require separate pipeline treatment and controls.【】【】3

Artifact collectors should connect source and build evidence to the releasable objects that are deployed or distributed. SBOM guidance distinguishes prebuild or source SBOMs, build-time SBOMs that record the exact components contributing to an artifact, and analyzed or postbuild SBOMs produced by binary analysis. Machine-processable formats and automation support are important because component data must be managed at scale and across organizational boundaries.【】4

Endpoint, runtime, and container collectors provide complementary views. Discovery guidance includes assets on end-user systems and servers, including applications, libraries, firmware, and software updates. Container security evidence also shows why runtime scope matters: a compromised runtime may threaten other containers and the host, while mandatory access controls and workload segmentation can limit the compromise scope. Runtime evidence should therefore include host, workload, image, namespace or segmentation context where available, rather than treating an image finding as an isolated artifact finding.【】【】15

Network collectors should cover observed protocols and connections, including TLS, SSH, and IPsec where those are in scope. The preliminary discovery material describes active and passive approaches, including asynchronous transfer of remote-user captures through a secure tunnel and analysis of historical traffic files. Network collection may therefore be real time, delayed, or historical; the record must preserve the observation mode and collection time.【】【】2

Cloud, PKI, KMS, IoT, and supplier surfaces require explicit ownership and integration boundaries. PKI evidence must relate certificates, keys, owners, and relying applications; compromise or loss of a certification authority private key can undermine confidence in certificates and revocation data. Key-management continuity also requires protecting associations between keys and owners, distribution records, and audit logs. IoT evidence should account for the product boundary, component responsibilities, customer or manufacturer control, and integration with enterprise asset, vulnerability, and log-management systems. Supplier evidence should include software provenance, release integrity, and the cryptographic content vendors may need to disclose when embedded cryptography is not discoverable by tools.【】【】【】【】678

3. Normalize evidence before correlation

Different collectors will describe the same object differently. The preliminary discovery architecture gives a simple example: one network platform may identify a host as host.example.com:443, while another may record only host.example.com. It therefore identifies a need for a common representation of discovery results and describes elements obtained from passive observation, active scanning, endpoint monitoring, or configuration information. Normalization should preserve the original observation while adding canonical identifiers and comparable fields; it should not erase source-specific detail.【】2

A normalized record should support at least the observed subject, cryptographic use, algorithm or protocol attributes, location, time, source, collection method, related asset, related identity or owner, and confidence. The source set does not prescribe a final schema, so these are architectural fields derived from the stated need to compare observations and link keys, certificates, applications, systems, and protocols. Where a relationship is inferred rather than directly observed, the record should say so rather than presenting the inference as fact.【】【】2

Correlation should join cryptographic findings with asset inventory, ICAM or IDAM, EDR, CDM, application and software-component data, and business information where available. Deduplication should be conservative: matching on a normalized host, port, certificate, artifact digest, application identifier, or other stable attribute can reduce duplicates, but ambiguous matches should remain separate and linked as possible equivalents. The purpose is enterprise risk management rather than isolated product reporting.【】【】12

4. Provenance, confidence, ownership, and access

Every finding needs provenance. At minimum, preserve the collector or source, collection method, observation time, source object, transformation history, and any relationship or deduplication decision. This is particularly important when evidence comes from binary analysis, passive traffic, configuration, vendor disclosure, or a preliminary architecture. SBOM guidance explicitly identifies provenance data as information to retain with software releases, and SSDF guidance recommends verifying tool integrity and provenance as well as monitoring tool logs for operational and security issues.【】【】49

Confidence should describe the strength of the observation, not the business importance of the asset. A directly observed protocol attribute, a configuration declaration, a binary-analysis result, and a vendor statement may warrant different confidence treatment. Discovery tools may fail to identify embedded cryptography inside products; the cited guidance therefore recommends asking vendors for lists of embedded cryptography. Such limitations belong in the record and in prioritization views.【】1

Ownership is a relationship that may cross organizational boundaries. A cryptographic asset can have separate technical, application, platform, PKI, KMS, data, and supplier owners. IoT guidance emphasizes coordination among manufacturers, customers, installers, and integrators, with responsibilities varying across the product lifecycle. The architecture should support multiple accountable parties, an escalation path, and an explicit state for unassigned ownership rather than silently assigning responsibility.【】8

Discovery metadata can reveal sensitive architecture, endpoint relationships, certificate associations, key-management context, and protected-data paths. Access control should therefore be applied to collection, transport, raw evidence, normalized records, exports, and administrative functions. The broader control evidence distinguishes functionality from assurance and treats access control, authentication, data security, platform security, and resilience as related cybersecurity outcomes. A practical design should use least-privilege access, separate administrative duties, and auditable changes, while preserving enough access for owners to act on findings.【】【】1011

5. Systems of record, APIs, and workflow

The discovery platform should not automatically become the authoritative system for every object. Define which system is authoritative for assets, identities, certificates, keys, software releases, vulnerabilities, ownership, remediation tasks, and risk acceptance. The discovery service can act as an evidence and relationship layer, publishing normalized observations and links to authoritative records. This avoids forcing one inventory to own data it cannot maintain and supports reconciliation when source systems disagree.【】【】12

APIs should expose ingestion, query, relationship, evidence, confidence, provenance, ownership, change, and export functions. They should support both current state and historical observations so that teams can determine whether a finding is new, persistent, remediated, or merely no longer observed. Workflow integration should send prioritized findings to the responsible team and receive status, evidence of remediation, exception, and reassignment updates. CI/CD integration is especially relevant because the cited DevSecOps guidance describes automated tools with feedback mechanisms throughout build, test, scan, package, deployment, and operations stages.【】【】32

Release and artifact records need durable retention. SSDF recommends securely archiving release files and supporting data such as integrity-verification and provenance information, with read-only access for necessary personnel and protection against unauthorized access. Key and certificate continuity planning also needs retention of distribution records, audit logs, ownership associations, and older software or hardware required to access protected information. Retention periods should therefore be risk- and lifecycle-based rather than limited to the latest scan result.【】【】97

6. Observability, trust boundaries, and resilience

The architecture itself needs observability. Monitor collector health, collection coverage, ingestion latency, rejected or malformed records, normalization failures, duplicate rates, API errors, authorization failures, storage capacity, and changes in source behavior. Tool and toolchain monitoring is explicitly recommended for operational and security issues, policy violations, and anomalous behavior. Observability as code is also identified as a distinct code type for continuous monitoring of application runtime state.【】【】

Use explicit trust boundaries between source environments, collectors, transport, processing, raw evidence, normalized inventory, workflow destinations, and administrative control planes. Collectors should receive only the permissions and data needed for their scope; transport and storage should protect confidentiality and integrity; and raw evidence should remain distinguishable from derived relationships. Zero-trust guidance for cloud-native applications emphasizes identity-based protection and, where applicable, network-based protections such as microsegmentation. These principles can inform discovery-service boundaries without implying a particular product design.【】【】

Resilience must cover collection outages, delayed network data, corrupted records, unavailable repositories, loss of audit logs, and recovery of key or certificate information. Key-management guidance warns about loss or corruption of distribution records, audit logs, and associations between keys and owners, and says contingency planning should address restoration of access, authorization, integrity protection, and encrypted communications without temporarily weakening protections. Discovery recovery should therefore preserve evidence integrity and access restrictions, not merely restore a dashboard.【】

7. A staged adoption path

A staged program reduces implementation risk. First, define the decision use cases: for example, locating cryptography protecting critical datasets, identifying vulnerable protocols, or connecting certificates and keys to applications. Second, establish the minimum normalized record, provenance rules, access model, ownership model, and authoritative-system boundaries. Third, onboard the highest-value collectors—typically source and build, artifact, endpoint, network, PKI, and KMS surfaces—while recording coverage gaps and uncertainty. This follows the evidence-supported need to prioritize systems and protocols protecting sensitive and critical datasets rather than treating every observation as equally urgent.【】

Next, add correlation with asset, identity, endpoint, and software inventories; integrate prioritization with existing enterprise dashboards and workflows; and validate deduplication against known systems. Then expand to runtime, cloud, IoT, and supplier surfaces, where control, visibility, and responsibility may differ. Finally, institutionalize continuous collection, drift detection, retention, observability, and recovery testing. Infrastructure-as-code guidance illustrates why drift matters: the deployed environment can diverge from its declared definition through console or command-line changes, so assurance requires a methodical drift-management process.【4】

Conclusion

An enterprise cryptographic-discovery architecture is a governed evidence pipeline: collect by surface, protect the metadata, normalize observations, correlate conservatively, preserve provenance and uncertainty, assign ownership, and publish actionable results through authoritative systems and workflows. Its value comes from relationships and decision context, not from a list of algorithms alone. A staged, vendor-neutral design can expand from the highest-risk code, artifact, endpoint, network, PKI, and KMS evidence to cloud, IoT, runtime, and supplier coverage while maintaining trust boundaries, observability, retention, and recovery.1249