AI Application Security Testing
(AI-AST™)

Securing the intelligence behind your AI — from data retrieval to decision.Artificial Intelligence is now integral to business-critical systems from chatbots to SOC assistants and decision engines that not only process data but also reason, generate, and act. As traditional SAST and DAST fall short in testing this new layer of intelligence, Entersoft’s AI-AST™ (AI Application Security Testing) emerges as the next evolution in AppSec, purpose-built to secure LLM-powered and RAG-based systems driving modern AI.

What Is AI-AST™?

AI-AST™ is an umbrella framework developed by Entersoft to extend security testing beyond code and APIs into the AI reasoning layer.

  • SAST finds issues in source code.
  • DAST scans runtime apps.
  • AIAST tests the intelligence layer the retrievers, vector databases, models, and agents that make decisions.
AI-AST™ Security Brief

It encompasses Seven specialized verticals:

AIAST testing workflow from architecture review to remediationRAG AST

RAG AST secures AI systems built on retrieval augmented generation pipelines protecting against data leakage, prompt injection, and manipulation attacks.

AI application security testing framework layers for RAG and LLMLLM AST

LLM AST secures applications powered by large language models protecting against prompt injection, data leakage, and model manipulation and attacks.

AIAST testing workflow from architecture review to remediationML AST

ML AST secures machine learning systems across training, inference, and deployment pipelines protecting against model abuse, poisoning, drift, and evasion.

AIAST testing workflow from architecture review to remediationAI API AST

AI API AST secures AI inference endpoints and service interfaces protecting against abuse, extraction, manipulation, cost exhaustion, and unauthorized access.

AIAST testing workflow from architecture review to remediationAGENTIC AST

Agentic AST secures autonomous and agent-based AI systems protecting against excessive agency, unsafe actions, privilege misuse, and decision manipulation.

AIAST testing workflow from architecture review to remediationAI Supply AST

AI Ecosystem Scan maps and evaluates organizational AI assets and dependencies protecting against blind spots, misconfigurations, unmanaged exposure, and systemic risk.

Why AI-AST™ Matters

AI introduces an entirely new attack surface

Prompt Injection

Attackers inject malicious instructions to bypass logic and policies.

Data Poisoning

Corrupt documents pollute retrieval results and model responses.

Hallucinations

Fabricated information misleads users and business processes.

Sensitive Data Leakage

Hidden PII or training data exposed through outputs.

Agent Abuse

Autonomous AI tools perform unauthorized actions.

Supply Chain Risks

Insecure libraries and models create unvetted dependencies.

AI-AST™ identifies and mitigates all these vulnerabilities bringing structure, repeatability & compliance to AI security.

OWASP LLM Top 10 & AI Governance Alignment

Entersoft’s AI-AST™ methodology maps directly to industry standards including

  • OWASP LLM Top 10 & ML Top 10 technical vulnerability coverage
  • NIST AI RMF 1.0 risk identification and measurement
  • ISO/IEC 42001 (2023) AI Management System controls
  • ISO/IEC 23894 (2023) AI risk management guidance

WHY CHOOSE ENTERSOFT AI-AST™

AI-powered security that thinks ahead

AI DRIVEN SECURITY

Built on 13 years of ethical hacking, AppSec, and SOC experience.

End-to-End Coverage

From model endpoint testing to RAG vector DB validation.

Secure by OWASP

Built on OWASP LLM Top 10 and ML Top 10 foundations.

AI Governance Ready

Mapped to ISO/IEC 42001 and NIST AI RMF 1.0 for enterprise compliance.

AI Threat Library

Continuous threat intelligence from live AI attack simulations.

AI-AST™ Testing Workflow

AIAST Testing Workflow ensures end-to-end security validation across all AI system layers. It systematically analyzes prompts, data retrieval, and model interactions for vulnerabilities. Each stage is tested for integrity, privacy, and resilience against AI-specific threats.

AI-AST™ Evaluation Framework

01

Architecture Review & Threat Modeling
Map AI data flows, trust boundaries, and third-party dependencies.

02

Attack Surface Discovery
Identify RAG, LLM, and agent interfaces exposed to users or APIs.

03

Adversarial Testing
Simulate prompt injections, data poisoning, and model abuse.

04

Vulnerability Validation
Execute controlled attacks and analyze LLM behavior changes.

05

Remediation & Retesting
Recommend fix steps and validate improvements.

06

Governance Mapping
Generate evidence aligned with OWASP & ISO standards.

Entersoft Delivering Excellence
Across Industries

Deliverables

  • AI Threat Model & Attack Surface Map
  • AIAST Findings Report (severity, CVSS score, description, remediation)
  • Proof-of-Concept Exploits & Test Harness
  • Risk Register & 30-day Remediation Plan
  • Compliance Mapping: OWASP + NIST + ISO
  • Attestation Pack (for client sharing or audit readiness)

Industries We Serve

  • Fintech & Banking AI Agents
  • Cybersecurity & SOC Automation Tools
  • Healthcare AI Assistants
  • EdTech & AI Tutors
  • Retail Chatbots & Recommendation Engines
  • Government AI Initiatives
Did you know?

Get Started with AI Application Security Testing

Your AI is your competitive advantage.
Make sure it’s also your most secure asset.

AI-AST™ because your model is your new attack surface.