// Adversarial AI testing. Real-world resilience.
AI Red Teaming
Expose weaknesses in model behavior, data pipelines, and AI-drive workflows before attackers do. Halborn's AI Red Teaming tests the full stack - models, inputs, integrations, and people – to strengthen trust and reduce real-world risk.
// Specialized AI offense to harden AI defense.
WHAT SETS HALBORN APART
AI-NATIVE EXPERTISE
Teams combine offensive security, ML engineering, and prompt-engineering knowledge to assess attacks unique to AI systems
END-TO-END SCOPE
Testing covers model behavior, data inputs, pipelines, API integrations, and human-in-the-loop risks — not just the model weights
RESPONSIBLE, CONTROLLED TESTING
Scoped, authorized adversarial tests that prioritize safety, data integrity, and operational continuity
Realistic Adversarial Scenarios
Evaluate risks from prompt injections, model poisoning, data poisoning, malicious LLMs, and AI-driven social engineering
Model & System-Level Findings
Identify behavioral failure modes, insecure integrations, and exploitable data flows affecting both model outputs and downstream systems
Actionable Mitigations
Deliver prioritized, developer-friendly fixes: prompt hardening, input sanitization, monitoring rules, and governance changes
Trust & Compliance Readiness
Demonstrate due diligence to stakeholders by validating AI controls, logging, incident playbooks, and governance around model use
