Input Validation

[Applicable to all providers (CSP, MP, OSP, AP) excluding AIC unless otherwise specified]
1. Define Input Validation Scope: Establish provider-specific processes for validating, filtering, modifying, or blocking inputs to protect against adversarial patterns, failure patterns, and unwanted behavior, as outlined in the provider-specific sections below. Ensure processes cover all input sources (e.g., user inputs, APIs, data feeds) throughout the application lifecycle, including development, deployment, and operation.

2. Input Validation Governance Structure: Establish clear roles and responsibilities for managing input validation processes, involving cross-functional teams (e.g., security, data science, development) and oversight by governance bodies. Define approval workflows involving senior management, security leads, and compliance teams to ensure alignment with organizational policies and regulatory requirements.

3. Input Validation Documentation Standards: Define structured documentation standards for input validation processes, including detailed procedures, adversarial pattern libraries, and mitigation strategies specific to each provider’s scope. Use consistent templates to document input validation rules, risk assessments, and response actions for detected threats to ensure traceability and auditability.

4. Input Validation Management Framework: Implement a structured review process for input validation policies and mechanisms. Conduct reviews and updates at least annually or following significant system changes (e.g., new input sources, updated threat models, or regulatory changes). Ensure alignment with relevant laws, regulations, and standards (e.g., GDPR, CCPA, ISO 27001, OWASP Top 10) and AI-specific frameworks such as NIST AI Risk Management Framework and OWASP LLM Top 10. Incorporate automated tools for real-time input validation and threat detection where possible.

5. Communication and Training Standards: Define requirements for communicating input validation policies, including formal distribution of documentation, mandatory training programs for developers and operators on adversarial pattern recognition and mitigation, and awareness campaigns for stakeholders. Establish standards for ensuring policy accessibility (e.g., internal portals) and comprehension across relevant teams.

7. Quality Control Standards: Define policies for quality assurance of input validation processes, including requirements for testing validation mechanisms (e.g., fuzz testing, adversarial simulation), monitoring input-related incidents, and validating mitigation effectiveness. Incorporate automated validation tools and anomaly detection systems to ensure robust protection against adversarial inputs and compliance with organizational policies.

1. Verify that the CSP has clearly defined processes, procedures, and technical measures in place which are addressing AI input validation. The documentation needs to clearly outline the scope as well as objectives, roles, and responsibilities.

2. Inspect these processes for compliance with applicable regulatory frameworks and AI best practices, specifically covering adversarial prompt attacks—including linguistic manipulations, logic manipulation, malicious programming code, adversarial token-based attacks, multi-language, and multi-modal threats.

3. Ensure that the CSP input validation practices consider the evolving AI threat scenario landscape and that a proactive AI Red Teaming is regularly performed.

4. Confirm that the input validation methods are active and perform detection, rejection, or sanitization of adversarial AI inputs across user-facing and API endpoints.

5. Review documented outputs of input validation assessments to ensure they are systematically analyzed and converted into actionable cybersecurity improvements.

6. Ensure that an ongoing monitoring of input validation mechanisms is in place, for evaluating their effectiveness through clearly defined, AI-specific security metrics and indicators (such as rate of detected adversarial inputs, prompt injection attempts).

7. Verify that validation measures are regularly reviewed and needed updates are implemented in a timely manner for effectively addressing continuous advancements in AI threat intelligence and adversarial attack methodologies.