AI & MLSecurity Testing
Most penetration testing firms still don't offer AI security assessment. I combine offensive security expertise with AI/ML knowledge to test LLM applications against the OWASP Top 10 for LLM Applications 2025, covering prompt injection, jailbreaking, model extraction, and training data poisoning before attackers or auditors find them first.
OWASP Top 10 for LLM Applications 2025
The 2025 edition defines the most critical security risks to LLM applications, from prompt injection and jailbreaking to model extraction and training data poisoning. I test every category with offensive techniques, not checklist reviews.
Prompt Injection
Manipulating LLM via crafted inputs
Insecure Output
Insufficient validation of model outputs
Training Data Poisoning
Compromising training data integrity
Model Denial of Service
Resource exhaustion attacks
Supply Chain
Third-party model and data risks
Sensitive Info Disclosure
Leaking confidential data
Insecure Plugin Design
Vulnerable LLM extensions
Excessive Agency
Overprivileged LLM capabilities
Overreliance
Unchecked dependence on outputs
Model Theft
Unauthorized model extraction
Comprehensive AI Security Testing
A three-pronged offensive assessment aligned to NIST AI RMF (AI 100-1), NIST Generative AI Profile (AI 600-1), and MITRE ATLAS for adversarial ML, covering application layer, model integrity, and data pipeline security.
Application Layer
Model Layer
Data Pipeline
Why Offensive AI Testing Matters
Automated scanners can't find prompt injection or model extraction. EU AI Act enforcement begins August 2025 for prohibited practices, with high-risk system requirements in August 2026, organizations need evidence-based security assessments, not governance paperwork alone.
Prompt Injection & Jailbreaking
Bypassing guardrails to extract data, execute tools, or override system instructions
Model Extraction
Reconstructing proprietary models through API queries, stealing your AI investment
Training Data Poisoning
Corrupting model behavior via compromised fine-tuning or RAG data sources
Regulatory Exposure
EU AI Act, NIST AI RMF, and emerging frameworks requiring demonstrable security controls
AI Systems I Test
Where traditional pentesters stop at web apps, I apply MITRE ATLAS adversarial ML techniques and real-world prompt injection chains to the systems your business actually depends on.
LLM Applications
ML Models
AI Infrastructure
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