The exposure of data while it moves between clients, hubs, brokers, and backend services because encryption or integrity protections are missing. In IoT systems, cleartext traffic can reveal credentials, device identifiers, and command payloads, while also making interception and message tampering far easier for a nearby attacker.
Expanded Definition
Insecure network transmission is the failure to protect data in motion between devices, brokers, gateways, and backend services. In NHI environments, the risk is not limited to confidential payloads. It also includes device identifiers, session tokens, API keys, command-and-control messages, and integrity-sensitive telemetry that can be read or altered in transit.
The term is broader than “no TLS” because weak cipher suites, broken certificate validation, skipped mutual authentication, and downgrade paths can leave traffic effectively exposed even when encryption is present. In practice, this is closely tied to zero trust expectations in NIST SP 800-207 Zero Trust Architecture, where trust is continuously evaluated rather than assumed because a packet is on an internal network. For NHI systems, the key question is whether the transport layer preserves confidentiality, authenticity, and message integrity across every hop.
Definitions vary across vendors when they blur transport security with application authorization, so practitioners should separate network protection from access control. The most common misapplication is treating “internal traffic” as inherently safe, which occurs when service-to-service links inside a cluster or IoT mesh are left unencrypted or unauthenticated.
Examples and Use Cases
Implementing secure transmission rigorously often introduces operational overhead, requiring organisations to weigh stronger assurance against certificate management, latency, and device compatibility.
- A sensor sends plaintext MQTT messages across a local network, allowing a nearby attacker to harvest device IDs and replay commands.
- An API gateway forwards bearer tokens over an unencrypted hop between edge and backend services, creating exposure even if the external client connection was protected.
- A robot controller uses TLS, but certificate validation is disabled, so a man-in-the-middle can impersonate the broker and inject unsafe instructions.
- An enterprise team reviews service-account traffic patterns after reading the Ultimate Guide to NHIs, then uses NIST SP 800-53 Rev 5 Security and Privacy Controls to map transport protection requirements to system baselines.
- A brokered automation flow between cloud functions and internal services is upgraded to mutual TLS so that both endpoints prove identity before any command payload is accepted.
In IoT and agentic systems, the challenge is often not whether encryption exists, but whether it remains enforced across constrained devices, legacy protocols, and intermediary brokers.
Why It Matters in NHI Security
Insecure network transmission turns ordinary traffic into a reconnaissance source for attackers. Once command payloads, secrets, or identity assertions can be observed or modified, service accounts and API keys become easier to steal, replay, or redirect. That risk is especially serious in environments where NHIs already outnumber human identities by 25x to 50x, as described in the Ultimate Guide to NHIs.
The governance issue is not just confidentiality. Message integrity failures can cause false telemetry, unsafe automation, or unauthorized privilege use that looks legitimate to downstream systems. Practitioners also need to consider that 90% of IT leaders say properly managing NHIs is essential for a successful zero-trust implementation, which makes secure transport part of the control plane rather than a network afterthought. This aligns with the expectations in NIST SP 800-207 Zero Trust Architecture and the broader control objectives in NIST SP 800-53 Rev 5 Security and Privacy Controls.
Organisations typically encounter the operational impact only after intercepted traffic, replayed commands, or a compromised broker exposes lateral movement, at which point insecure network transmission becomes operationally unavoidable to address.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0, NIST Zero Trust (SP 800-207), NIST SP 800-63 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-06 | Transport exposure weakens NHI credential and token protection in transit. |
| NIST CSF 2.0 | PR.DS-2 | Protects data in transit against unauthorized disclosure and tampering. |
| NIST Zero Trust (SP 800-207) | SC-7 | Zero Trust assumes no implicit trust in network location or path. |
| NIST SP 800-63 | Identity assertions and authenticators must not be exposed during transmission. | |
| NIST AI RMF | GV.4 | AI risk management includes securing data flows that carry model inputs and outputs. |
Protect identity proofing artifacts and authenticators with strong transport security wherever they travel.
Related resources from NHI Mgmt Group
- Who is accountable when credit card data is exposed through insecure storage or transmission?
- Why has identity replaced the network perimeter as the primary security boundary?
- Why are identity-based attacks growing faster than traditional network attacks?
- What is the difference between network controls and identity controls for infrastructure access?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on August 26, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org