Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
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Database security (encryption, access control, injection prevention), data governance (lineage, quality, MDM), and compliance frameworks (GDPR, CCPA, HIPAA)
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安装前可以查看交给 AI 代理的指令内容。
Layered security, each layer provides independent protection:
Encrypts DB files on disk without application changes. Encrypts data pages before writing, decrypts on read into memory. AES 128/256-bit symmetric encryption. Transparent to applications.
-- SQL Server TDE (key hierarchy: Service Master Key -> DB Master Key -> Certificate -> DEK)
CREATE DATABASE ENCRYPTION KEY WITH ALGORITHM = AES_256
ENCRYPTION BY SERVER CERTIFICATE TDE_Cert;
ALTER DATABASE [YourDB] SET ENCRYPTION ON;
-- PostgreSQL: pgcrypto for column-level, full TDE in v17+ | Oracle: ALTER SYSTEM SET ENCRYPTION KEY
sslmode=require in PostgreSQL)Assign permissions to roles, roles to users. Standard in all major DBs.
-- PostgreSQL RBAC: create roles with specific grants, assign to users
CREATE ROLE app_readonly; GRANT SELECT ON ALL TABLES IN SCHEMA public TO app_readonly;
CREATE ROLE app_readwrite; GRANT SELECT, INSERT, UPDATE ON ALL TABLES IN SCHEMA public TO app_readwrite;
GRANT app_readonly TO reporting_user; GRANT app_readwrite TO application_user;
Access decisions based on attributes of user, resource, environment. More flexible than RBAC for complex scenarios (multi-tenant, data classification).
# VULNERABLE - string concatenation (SQL injection risk)
query = f"SELECT * FROM users WHERE name = '{user_input}'"
# SAFE - parameterized (all languages: Python %s, Java ?, C# @param, Node.js $1)
cursor.execute("SELECT * FROM users WHERE id = %s AND status = %s", (user_id, 'active'))
Input validation: whitelist allowed chars/formats | Stored procedures: reduce direct SQL exposure | Least privilege: no DDL for app accounts | WAF rules | Never expose DB error messages to end users
Track data from source through transformations to consumption:
Purpose: Regulatory compliance (GDPR Article 30) | Impact analysis (downstream schema change effects) | Root cause analysis (bad data origin) | Audit trails
| Dimension | Definition | Example Check |
|---|---|---|
| Accuracy | Correctly represents real-world entities | Email format validation |
| Completeness | Required fields populated | NOT NULL checks, completeness % |
| Consistency | Same data across systems agrees | Cross-system reconciliation |
| Timeliness | Current and available when needed | Freshness SLAs |
| Uniqueness | No unintended duplicates | Duplicate detection on business keys |
| Validity | Conforms to defined rules/formats | Range checks, enum validation |
Establish single source of truth for core entities (customer, product, location) | Define golden record resolution rules | Implement data stewardship roles | Use MDM platform or reference data services
Right to know (disclose collected data) | Right to delete | Right to opt-out of data sale | Non-discrimination regardless of privacy choices
PHI encryption at rest and in transit | Role-based access with minimum necessary standard | Audit all PHI access | Business associate agreements for third-party processors
3 copies of data | 2 different storage types | 1 copy offsite
Test recovery regularly (monthly minimum) | Document RTO and RPO | Encrypt backup files | Store encryption keys separately from backups
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Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
中文简介正在准备中。当前显示原文说明。
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
中文简介正在准备中。当前显示原文说明。
Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof
中文简介正在准备中。当前显示原文说明。
Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement
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5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance
中文简介正在准备中。当前显示原文说明。
Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.
中文简介正在准备中。当前显示原文说明。