Engineering-driven adversarial evaluation for the world's most capable foundation models. We identify bespoke logic leaks, jailbreaks, and PII extraction vectors that traditional benchmarks miss.
Our security researchers go beyond simple prompts to map the entire latent risk space of your model.
Identifying character-level perturbations and gradient-based suffixes that can trigger prohibited responses by bypassing semantic safety layers.
Probing the model's ability to reconstruct harmful instructions from non-harmful atomic components through multi-turn, high-reasoning interactions.
Stress-testing model weight boundaries to ensure that pre-training data memorization does not leak sensitive or personally identifiable information.
We don't just find bugs; we help you build a fortress. Our reporting is structured to meet the most demanding regulatory and enterprise safety requirements.
Fully aligned with NIST 100-1 guidelines for secure generative AI deployment.
Providing the technical evidence required for high-risk system conformity assessments.
High-level summary for board and legal review.
Complete prompt/response traces for engineering teams.
Tactical instructions for fine-tuning and guardrail hardening.
Common inquiries regarding our adversarial evaluation methodologies and secure data protocols.