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Cutting-Edge AI Security Testing

AI Security
Testing

In-depth security assessment of AI/ML systems, large language models, and generative AI applications to identify unique vulnerabilities in modern AI deployments

OWASP
LLM Top 10 Coverage
CSA
AI Red Teaming Guide
MITRE
ATLAS Framework
20+
Years Experience

Our AI Security Approach

KoreLogic's AI security testing methodology addresses the full AI stack - from data sources and model infrastructure through agents, APIs, and integration points - guided by CSA, OWASP, MITRE ATLAS, NIST, and BIML frameworks.

LLM Vulnerability Assessment

Thorough testing against the OWASP LLM Top 10 including prompt injection, insecure output handling, training data poisoning, and model denial of service attacks.

Adversarial AI Testing

Advanced adversarial attacks including evasion attacks, model extraction, membership inference, and robustness testing of AI decision systems.

Full-Stack AI Infrastructure

End-to-end assessment across the AI stack: data and data sources, model serving platforms, training environments, AI-augmented applications and APIs, and AI integration points within the broader enterprise architecture.

Agentic AI Assessment

Security evaluation of autonomous AI agents and multi-agent workflows - agent sandboxing, constraint enforcement, action provenance, MCP protocol security, prompt and context integrity, and memory mode isolation.

AI Stack Coverage

Data and data sources
Agents, prompts, contexts, and memory modes
MCP protocols and tool integrations
AI-augmented applications and APIs
Models and algorithms
AI infrastructure and integration points

AI Security Testing Services

Four core service lines covering the full AI security landscape - from architecture review through hands-on penetration testing of agentic systems and vendor-developed AI products.

AI Security Architecture Review

Comprehensive review of your AI deployment architecture across the full stack - data sources, models, agents, APIs, and integration points - to identify systemic security risks before they become vulnerabilities.

  • - Full-stack AI architecture assessment
  • - Data pipeline and model supply chain review
  • - AI integration point analysis
  • - Governance and compliance posture evaluation

Penetration Testing of AI-Augmented Applications

Hands-on penetration testing of web applications, APIs, and services that incorporate LLMs, chatbots, or other AI components - tested against OWASP LLM Top 10 and traditional web application attack vectors.

  • - Prompt injection and jailbreaking
  • - Insecure output handling and data leakage
  • - LLM-specific attack chains
  • - Traditional web app vectors at AI integration points

Agentic AI Penetration Testing

Security testing of autonomous AI agents and multi-agent systems using CSA AI Red Teaming guidance - evaluating sandboxing, constraint enforcement, tool use security, and action provenance across agent architectures.

  • - Agent sandboxing and isolation testing
  • - MCP protocol and tool integration security
  • - Code and action provenance verification
  • - Multi-agent trust boundary validation

Product Security of Vendor AI Solutions

Independent security evaluation of vendor-developed AI products and platforms your organization is considering or already deploying - assessing model robustness, data handling, and supply chain integrity.

  • - Vendor AI product security assessment
  • - Model robustness and adversarial testing
  • - AI supply chain and third-party risk
  • - Privacy, bias, and compliance evaluation

Supporting Capabilities

Specialized expertise that underpins each of our four core service lines - from adversarial model testing and data pipeline security through governance and regulatory compliance.

ML Model Security

Advanced adversarial testing of machine learning models and AI decision systems to evaluate robustness against targeted attacks.

  • - Adversarial example generation
  • - Model extraction and theft attacks
  • - Membership inference testing
  • - Evasion and robustness assessment

Training Data Security

Assessment of training data integrity, privacy protection, and pipeline security to prevent data poisoning and unauthorized exposure.

  • - Data poisoning detection
  • - Privacy leakage assessment
  • - Data provenance verification
  • - Sensitive data exposure analysis
  • - Training pipeline integrity

AI Governance & Compliance

Evaluation of AI governance posture and regulatory readiness aligned with established risk management frameworks.

  • - NIST AI RMF alignment
  • - BIML framework assessment
  • - Regulatory compliance evaluation
  • - Bias and fairness testing
  • - Explainability assessment

Assessment Deliverables

Executive Summary

High-level overview of AI security risks, business impact, and strategic recommendations

Technical Findings

Detailed analysis of AI vulnerabilities, attack vectors, and proof-of-concept demonstrations

AI Security Roadmap

Strategic roadmap with prioritized recommendations

Ongoing Support

Post-assessment remediation guidance and follow-up testing recommendations

Professional Reports

Detailed AI security assessment deliverables that provide actionable insights and strategic recommendations.

Business risk analysis and compliance implications
Prioritized action plan with resource requirements
Security monitoring and continuous improvement guidance

Ready to Strengthen Your Security?

Our AI security experts will help you identify and mitigate risks across your AI systems, models, and agentic workflows.

Discuss Your Security Requirements View All Penetration Testing Services

Confidential consultation — Expert recommendations — Detailed reporting