AI Red Teaming & Security Assessments
Test AI models, applications, and agentic workflows to expose vulnerabilities before adversaries exploit them.
Common Challenges
- Prompt injection and jailbreak paths that defeat guardrails
- Insecure tool use and excessive agency in agentic workflows
- Sensitive data exposure through model context or training data
- Insufficient logging, monitoring, and human oversight of AI output
- Ad hoc AI review with no repeatable test methodology
How We Support
Model the threat surface across the application, model, and data layers
Exercise adversarial prompts, injection paths, and tool-use boundaries
Assess data handling, context isolation, and output filtering
Review governance, logging, and human-in-the-loop controls
Retest remediated findings to confirm closure
Other Core Capabilities
FEDERAL COMPLIANCE
CMMC & NIST SP 800-171 Readiness
Identify compliance gaps, strengthen security controls, and prepare evidence to support applicable CMMC assessment requirements.
View CapabilityZERO TRUST
Zero Trust & Secure Cloud Architecture
Strengthen identity, access, network segmentation, and cloud security to reduce unauthorized access and infrastructure exposure.
View CapabilityCYBER DEFENSE
Threat Detection Engineering & SOAR
Improve threat visibility, accelerate detection, and automate response workflows to reduce the time adversaries can operate undetected.
View CapabilityReady to strengthen your ai security posture?
Contact us to discuss scope, timeline, and what a measurable engagement looks like for your program.