// Adversarial AI testing. Real-world resilience.
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.
Teams combine offensive security, ML engineering, and prompt-engineering knowledge to assess attacks unique to AI systems
Testing covers model behavior, data inputs, pipelines, API integrations, and human-in-the-loop risks — not just the model weights
Scoped, authorized adversarial tests that prioritize safety, data integrity, and operational continuity
Evaluate risks from prompt injections, model poisoning, data poisoning, malicious LLMs, and AI-driven social engineering
Identify behavioral failure modes, insecure integrations, and exploitable data flows affecting both model outputs and downstream systems
Deliver prioritized, developer-friendly fixes: prompt hardening, input sanitization, monitoring rules, and governance changes
Demonstrate due diligence to stakeholders by validating AI controls, logging, incident playbooks, and governance around model use
Monetari
Case Study: Supporting a Large Settlement and Clearing House with Secure by Design Architecture
Case Study: Securing $360B+ in Tokenized Domains with Doma Protocol
Case Study: Scaling a G-SIB's Custody Platform Through Secure by Design Engagement
Case Study: Hardening Infrastructure for a B2B Crypto Custody Provider
Monetari
Saucerswap Labs
TruYields
Arkonix
Catapult Trade
$1T
Value protected
5
Publicised zero days
3K+
Assessments completed
100+
Security practitioners
800+
Happy clients
15
Platforms & languages