It focuses on how attackers interact with your AI system only through its public or internal API surface exactly how real attacks occur.
AI API - Abuse Protection
Securing AI systems exposed through APIsModern AI applications expose intelligence through APIs powering scoring, recommendations, moderation, fraud detection, and AI-driven SaaS features. Treating these inference endpoints like traditional APIs is a critical mistake. AI APIs behave differently and can be probed, abused, and economically exploited in ways conventional API testing cannot detect. Entersoft’s AI API AST is purpose-built to secure AI inference endpoints, even when the underlying model remains a black box.What Is AI API AST?
AI API AST is a dedicated security testing discipline under Entersoft’s AI Application Security Testing (AIAST) framework.
- API Pentesting checks endpoints, auth, and parameters
- AI API AST evaluates how inference behavior can be abused
Why AI APIs Need Specialized Security Testing
AI APIs expose decisions and predictions, making inference endpoints vulnerable to repeated abuse.
Extract model behavior and logic
Manipulate outputs using crafted inputs
Exhaust compute budgets through query flooding
Abuse APIs to reverse-engineer proprietary models
Trigger incorrect decisions at scale
Bypass safeguards to elicit restricted or unsafe responses
Traditional API testing misses intelligence abuse AI API AST closes the gap.
How AI API AST Works
AI API AST begins by understanding how your inference endpoints are consumed in the real world.
Access control
Analyze how APIs are accessed, authenticated, and misused across different usage patterns.
Rate Limiting
Evaluate throttling controls to prevent abuse, denial of service, and cost-exhaustion attacks.
Input Boundaries
Test how varied, malformed, and edge-case inputs impact model behavior and stability.
Output Sensitivity
Assess response reliability and identify unintended data leakage or sensitive inference exposure.
Abuse detection and anomaly monitoring
Identify abnormal usage patterns, automation, and probing behavior indicative of AI API abuse.
Built for AI Governance and Enterprise Risk
AI API AST is designed to support enterprise governance, regulatory alignment, and risk oversight for AI-powered systems. It aligns with leading global frameworks and standards, enabling organizations to operationalize responsible and secure AI at scale.
- OWASP LLM Top 10: Addresses critical AI threats such as model theft, excessive agency, prompt manipulation, and unsafe output handling that traditional security testing fails to uncover.
- NIST AI Risk Management Framework (AI RMF): Supports structured identification, assessment, and mitigation of AI risks across governance, measurement, and operational controls.
- ISO/IEC 42001 and ISO/IEC 23894: Enables compliance with AI management system requirements and AI risk governance across the full AI lifecycle.
- Enterprise Risk & Compliance Programs: Integrates seamlessly into existing GRC workflows, helping security, legal, and risk teams assess AI exposure alongside traditional cyber risks.
- Audit, Reporting, and Executive Visibility: Produces defensible security evidence and reporting to support audits, regulatory reviews, and board-level risk discussions.
AI-Specific Risks We Test in AI APIs
AI API AST focuses on risks unique to inference-based systems, including:
- Model Extraction – reconstructing model logic through systematic querying
- Inference Abuse – manipulating predictions or classifications
- Query Flooding – bypassing rate limits to exhaust resources
- Cost Exhaustion – forcing excessive compute or token usage
- Output Manipulation – influencing downstream decisions
- Silent Misuse – attacks that appear as “valid API traffic”
These risks often bypass traditional security alerts entirely.
Security Beyond the Endpoint
AI API AST also evaluates the control plane around inference, including:
- Assess whether API keys are properly scoped, isolated, and restricted to prevent over-privileged access and lateral misuse across AI services and tenants.
- Test how rate limiting and throttling controls behave under sustained, automated, and burst traffic designed to exhaust compute resources or bypass usage policies.
- Evaluate the effectiveness of monitoring rules, behavioral baselines, and alert thresholds in identifying probing, scraping, and model abuse activity.
- Verify that inference activity is logged with sufficient context to support traceability, incident response, compliance audits, and regulatory reporting.
Why Enterprises Choose Entersoft for AI API Security
Organizations trust Entersoft because we.
AI Native Testing
Test AI APIs the way attackers abuse them
Impact Driven
Go beyond authentication and schema validation
Actionable Fixes
Deliver evidence-based findings with business impact
Audit Ready
Provide clear remediation guidance for AI teams
When Do You Need AI API AST?
AI API AST is essential if:
Your AI is exposed through public or partner APIs
Your pricing or infrastructure depends on inference usage
Your AI influences business-critical decisions
Your system relies on third-party or hosted AI models
