Credential entry rate measures how often users submit usernames, passwords, or other login details to a fake phishing page during testing. It is a useful behaviour metric because it shows whether training has translated into safe action, especially under pressure from convincing lures or impersonation.
What Credential Entry Rate Measures
credential entry rate is a behavioural test metric, not a technical exposure metric. It measures how often people submit login details to a simulated phishing page, which helps show whether awareness training is changing real-world judgement under pressure.
The value of the metric is that it captures a concrete action, not just a stated belief. A lower rate suggests users are more likely to pause, verify, or avoid handing over credentials when a lure looks plausible.
How to Interpret the Metric
This measure is best read as a signal of user susceptibility in a specific test scenario. It can be influenced by the quality of the lure, the timing of the exercise, the audience, and whether the test is measuring first-time exposure or repeat behaviour.
Because it is a rate, the denominator matters. A meaningful result should be tied to a defined population and testing window so teams can compare campaigns without confusing one-off exceptions with a stable pattern.
Why It Matters for Security Awareness
Credential entry rate matters because phishing succeeds when a user crosses the trust boundary and voluntarily gives up sensitive login material. A test that shows frequent credential submission indicates that the organisation still has a human behaviour gap, even if formal policy and training are in place.
The metric is especially useful when combined with follow-up controls such as reporting workflows, simulated phishing education, and identity protection measures. It does not prove compromise on its own, but it does show whether users are likely to provide an attacker with the first step of account takeover.
Common Uses and Limitations
Teams use credential entry rate to compare campaigns, track change over time, and identify which populations need more reinforcement. It is also useful for distinguishing between training that is merely remembered and training that is actually applied in a realistic moment.
The limitation is that the number can be misleading if it is treated as a standalone score for human risk. A well-designed phishing simulation should be interpreted alongside click rate, report rate, and the realism of the exercise itself, because a single metric rarely explains the full behavioural picture.
Risk and Threat Considerations
High credential entry rate indicates a larger attack surface for phishing, account takeover, and downstream misuse of stolen credentials. The risk is not the metric itself, but what it reveals about the likelihood that a convincing lure can capture usable login material.
Failure mechanism: An attacker presents a believable login prompt, the user enters credentials, and those secrets are reused for initial access, session theft, or follow-on impersonation.
Impact: Stolen credentials can lead to mailbox compromise, SaaS access, internal pivoting, fraud, and broader identity abuse if the same username and password are valid elsewhere.
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 addresses the attack and risk surface, while NIST SP 800-63, NIST SP 800-53 Rev 5 and CIS Controls v8 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-04 — Insecure Authentication | Credential submission in phishing tests reflects weak auth judgement under deceptive prompts |
| NHI-02 — Secret Leakage | Entered usernames and passwords can be exposed to a fake page and reused by attackers | |
| Recommendation — Measure and harden authentication behaviour against deceptive login prompts. Reduce opportunities for credential capture and reuse. | ||
| NIST SP 800-63 | Digital Identity Guidelines | Phishing-resistant authentication and verifier assurance directly reduce credential capture risk |
| Recommendation — Adopt phishing-resistant authenticators and stronger verifier practices. | ||
| NIST SP 800-53 Rev 5 | IA-2 — Identification and Authentication (Organizational Users) | User login behaviour and credential use map directly to organizational authentication controls |
| Recommendation — Strengthen user authentication controls and reduce reliance on reusable passwords. | ||
| CIS Controls v8 | CIS-5 — Account Management | Credential entry tests reveal account misuse exposure that account controls must limit |
| Recommendation — Enforce strong account controls and rapid response to suspected credential compromise. | ||
Practitioner Guidance
Why practitioners should care: Treat credential entry rate as a behaviour indicator that should shape training priorities, simulation design, and executive reporting. A single percentage is less important than whether the rate is trending down across realistic scenarios.
What to watch for: Look for repeated submission on the same lure style, spikes after policy changes, or weak performance in high-pressure campaigns that imitate password resets, shared services, or brand impersonation.
Practitioner takeaway: Use the metric to target the weakest behaviour pattern, then validate whether the change survives a better lure, not just a more obvious one.
Related resources from NHI Mgmt Group
- How should security teams reduce breach risk when known vulnerabilities and credential abuse remain the main entry paths?
- What should security teams do when a phishing report includes a click or credential entry?
- How should IAM leaders reduce breach risk when credential misuse is the dominant entry point?
- How should teams add authentication to developer documentation portals without forcing repetitive credential entry?
