Zero Trust Fail-Open and Anomaly Handling Verification Dataset

#Code verification #Exception path analysis #Security defect detection #Root-cause analysis #Zero Trust access control #Identity and device verification #Failure security audits #Security code review

6470
0.5GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-03

AI Analysis & Value Prop

Includes source code and analysis information for Zero Trust policy, identity, and device assessment services under timeouts, service outages, error responses, and partial failures. The data focuses on fail-closed security behavior and helps identify fail-open defaults, skipped checks, status misclassification, and recovery logic defects in exception paths. It supports security code review, access control verification, and failure root-cause analysis.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
evidence	array	Code locations, behavioral evidence, risk explanations, and remediation suggestions supporting the analysis findings.
risk_level	string	Risk rating based on issues such as fail-open behavior, skipped checks, status misclassification, and recovery defects.
source_code	string	Zero Trust service source code for analysis, including failure handling, policy decisions, identity verification, or device assessment logic.
service_context	object	Original context describing the service, dependent components, failure type, and expected security properties.
source_language	string	Programming language used by the source code, such as Python, JavaScript, or TypeScript.
analysis_summary	string	Combined findings on exception path behavior, access decisions, and security risks.
decision_outcome	string	Final decision inferred from the source code for the failure scenario, such as deny, allow, challenge, fallback, or unknown.
anomaly_categories	array	Set of categories describing detected exception-handling issues.
security_fail_closed	boolean	Indicates whether the system denies access or blocks operations when a dependency fails or its result is uncertain.
check_bypass_detected	boolean	Indicates whether an exception path skips required identity, policy, device status, or other security checks.
default_allow_detected	boolean	Indicates whether access or an operation is incorrectly allowed by default during an exception, timeout, or dependency outage.
recovery_logic_defect_detected	boolean	Indicates whether retry, fallback, cache recovery, circuit breaker, or exception handling logic can disable security controls or restore an incorrect state.
status_misclassification_detected	boolean	Indicates whether a timeout, error, unknown result, or partial success is incorrectly treated as success, authentication, or authorization.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: It includes source code related to Zero Trust policy, identity, or device assessment, along with service context, anomaly analysis, security decisions, risk categories, and code evidence. Key scenarios include timeouts, unavailable services, error responses, and partial failures.

Which analysis tasks does it support?: Use it to verify fail-closed behavior during failures and detect fail-open defaults, skipped security checks, status misclassification, and recovery logic defects. It also supports exception path analysis, security code review, and root-cause analysis.

Is the dataset limited to a programming language or size?: Each record can include source language information, which supports language-based filtering and analysis. The dataset description does not specify a fixed programming language, sample count, or code volume; refer to the available records for actual coverage.

How can I access the dataset, and what licensing applies?: Check the current product page or the provider's published channels for access methods, available formats, and license terms. Before commercial training, redistribution, or security research use, confirm the applicable permissions and any restrictions on source code.

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Cite this Work

@dataset{Mobiusi2026,
  title={Zero Trust Fail-Open and Anomaly Handling Verification Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/0d08b504e7b80d729ca509518446fc0d},
  urldate={2026-10-27},
  keywords={Zero Trust dataset,fail-open detection,exception handling verification,fail-closed security,access control code review,identity verification security,device assessment failures,code security analysis},
  version={1.0}
}

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