AI Red Teaming
Automated agentic AI stress testing for your guardrails
Prompt Shields automates adversarial testing using AI agents built on Azure AI Foundry to systematically break your guardrails before attackers do.
We simulate sophisticated attack patterns across prompts, agents, tools, and data access paths with intelligent adaptation and persistence.
Automated testing • Adversarial agents • Pre-production validation
1000+
attack patterns tested
4x
critical vulnerabilities found
99.9%
guardrail effectiveness tested
100%
results validated & actionable
Why AI Red Teaming
Benefits of automated agentic stress testing
Systematic, intelligent adversarial testing that goes beyond manual efforts to validate guardrail robustness.
Automated Scale
AI agents run thousands of adversarial tests automatically, far exceeding manual testing capacity.
- Parallel multi-agent testing
- 24/7 continuous testing
- Comprehensive coverage
Intelligent Adaptation
Agents learn and adapt attack strategies based on system responses, discovering compound vulnerabilities.
- Response-aware pivoting
- Multi-step attack chains
- Emergent pattern discovery
Pre-Production Assurance
Validate guardrail effectiveness before production deployment, eliminating critical security gaps.
- Structured validation
- Risk quantification
- Compliance alignment
Testing Focus Areas
What we systematically test
Our agents target AI-specific failure modes that traditional security testing does not cover.
Large Language Models and Copilots
- •Prompt injection and instruction override
- •Jailbreak attempts and policy bypass
- •Data extraction through indirect prompts
- •Hallucination and misleading output risks
Agentic AI workflows
- •Agent tool misuse and exploitation
- •Over-privileged access paths
- •Unsafe chaining between agents
- •Unintended data aggregation across sources
Retrieval-Augmented Generation (RAG)
- •Sensitive data exposure via context windows
- •Role confusion and access control failures
- •Poisoned or manipulated retrieval sources
Our Approach
How automated agentic red teaming works
Deploy Adversarial Agents
Launch intelligent agents that generate and adapt adversarial prompts based on system responses.
- Multi-model agent orchestration
- Continuous adaptation strategies
- Targeted guardrail bypass attempts
Monitor & Capture Results
Record all agent interactions, guardrail triggers, and system behaviors for comprehensive analysis.
- Full interaction logging
- Guardrail effectiveness tracking
- Anomaly detection
Validate & Deliver
Human specialists verify findings and deliver actionable recommendations with remediation paths.
- Expert verification & analysis
- Business impact assessment
- Remediation guidance
Technology Stack
Built on Azure AI Foundry
Enterprise-grade infrastructure for automated AI security testing.
Azure-native agents
- Azure OpenAI model integration
- Azure AI Agent Service orchestration
- Multi-model agentic testing
- Enterprise isolation & control
Enterprise security
- Zero customer data outside agreed boundaries
- Complete test/production separation
- Microsoft security & compliance alignment
- Audit-ready logging and reporting
Deliverables
What you receive
Actionable outcomes designed for security teams and board-level reporting.
Comprehensive Finding Reports
Detailed documentation with reproduction steps, business impact, and severity assessment.
Risk Prioritization Matrix
Severity scoring mapped to your risk framework and business context.
Remediation Roadmap
Prioritized action items with implementation guidance and effort estimates.
Retest Engagement
Follow-up testing to validate that remediation efforts have closed identified gaps.
Use Cases
When to run red team engagements
Pre-Launch Validation
Before deploying customer-facing or high-stakes AI systems
Agentic Workflow Launch
When introducing new agentic patterns or tool integrations
Copilot Deployments
During internal Copilot rollouts or Microsoft AI integrations
Post-Update Validation
After guardrail changes, model updates, or policy revisions
Regulatory Compliance
For AI governance, compliance, and audit requirements
Architecture Changes
When modifying RAG, data access, or system architecture
Integrated Approach
Red teaming feeds the defence loop
Red team findings drive continuous improvement in your guardrails and defences.
Test findings are immediately actionable for:
Guardrail tuning
Strengthen policies based on bypasses discovered
Control refinement
Deploy additional controls or constraints
Governance tracking
Monitor improvement via continuous retesting
This creates a virtuous attack-defence cycle that continuously strengthens your AI security posture.
Complementary Approaches
How red teaming complements exploratory testing
AI Red Teaming
Automated, goal-oriented adversarial testing to validate guardrails before production.
- •Point-in-time guardrail validation
- •Structured attack scenarios
- •Pre-deployment assurance
Exploratory Testing
Continuous discovery-focused testing for ongoing production monitoring.
- •Continuous coverage
- •Adaptive discovery approach
- •Post-deployment monitoring
Best results combine both approaches
Red teaming validates guardrails before launch, exploratory testing discovers emerging risks in production.
Stress-test your AI guardrails
Discover how your guardrails hold up under systematic adversarial pressure before attackers do.