Deceptive practices risk arises when a company’s public security claims do not match the actual behaviour of its products or services. In regulated environments, that mismatch can trigger enforcement even if the underlying technical change was made for operational or political reasons.
Expanded Definition
Deceptive practices risk is the exposure created when a company’s public claims about security, privacy, identity controls, or operational safeguards do not match how systems actually behave. In NHI and agentic AI environments, that gap can involve service account governance, secret handling, access revocation, logging, or tool permissions. The issue is not limited to outright fraud. It also includes misleading omissions, stale documentation, and security statements that are technically true in a narrow sense but false in practical effect. Regulatory scrutiny often turns on what an organisation represented to customers, partners, or regulators, versus what was demonstrably enforced. Guidance varies across jurisdictions, but the underlying expectation is consistent: claims should be supportable, current, and aligned to real control operation. For security teams, this makes disclosure accuracy part of governance, not a marketing afterthought, and it connects directly to NIST Cybersecurity Framework 2.0 style integrity and accountability expectations. The most common misapplication is treating a planned control as if it were already effective, which occurs when policy language is published before implementation or verification is complete.
Examples and Use Cases
Implementing deceptive-practices controls rigorously often introduces documentation and verification overhead, requiring organisations to weigh speed of communication against the cost of proving that claims remain accurate.
- A SaaS provider advertises that API keys are rotated automatically, but only a subset of environments actually enforce rotation. That mismatch becomes risky during procurement reviews and incident disclosures, especially when compared against the governance issues discussed in Top 10 NHI Issues.
- An AI platform claims tool access is restricted by least privilege, yet long-lived service tokens still retain broad permissions after deployment changes. That creates a representation problem under the control logic reflected in NIST SP 800-53 Rev 5 Security and Privacy Controls.
- A company states that secrets are stored only in a vault, while CI/CD variables and repository config files still contain active credentials. The operational gap between claim and reality mirrors the risk patterns described in the Ultimate Guide to NHIs - Key Challenges and Risks.
- A regulator asks whether offboarding immediately revokes machine identities, but the team only deactivates them in some business units. The answer may be inaccurate even if the organisation believes its process is “mostly” complete.
Why It Matters in NHI Security
Deceptive practices risk matters because NHI security failures are often invisible until an outage, breach, or audit reveals them. NHIMG reports that 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, which means public claims about mature secret governance are easy to overstate and difficult to defend when challenged. That reality makes transparency around service accounts, token rotation, vault enforcement, and revocation workflows central to trust. The same applies to Ultimate Guide to NHIs - Why NHI Security Matters Now, which frames NHI sprawl as a systemic governance problem rather than a narrow technical one, and to OWASP NHI Top 10, where weak identity controls and misrepresented protections create compound risk in agentic systems. In practice, deceptive-practices exposure often becomes material after a breach report, customer complaint, or regulator inquiry, at which point the accuracy of prior security claims 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 and OWASP Agentic AI Top 10 address the attack and risk surface, while NIST CSF 2.0, NIST SP 800-53 Rev 5 and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.OV-01 | Security claims must reflect actual governance and oversight outcomes, not aspirational policy. |
| NIST SP 800-53 Rev 5 | AU-16 | Audit and accountability expectations support accurate representation of control operation. |
| OWASP Non-Human Identity Top 10 | NHI-02 | Secret and identity mismanagement often drives misleading security claims in NHI programs. |
| OWASP Agentic AI Top 10 | A10 | Agentic systems can expose misleading claims when tool permissions exceed documented bounds. |
| NIST AI RMF | AI risk management includes truthful communication about system capabilities and limits. |
Verify that published security statements are backed by monitored, operating controls and documented evidence.
Related resources from NHI Mgmt Group
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Reviewed and updated by the NHIMG editorial team on July 14, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
