Rivac AI LabsAI/LLM Security Red-Teaming
A deployed LLM or agent is a new attack surface, and the exploits that matter (prompt injection, jailbreaks, data exfiltration through crafted inputs, tool-use abuse) don't show up in a standard penetration test built for traditional web applications. We run adversarial testing specifically designed for AI systems, attempting to break your models and agents the way a real attacker or a malicious user would, across the specific ways your system is actually deployed and integrated. Every finding comes with a reproducible attack case and a concrete remediation recommendation, not just a severity score. Clients use this to close AI-specific security gaps before an attacker (or a curious user posting screenshots online) finds them first.
This is a capability we deliver for you as a service, not a role we’re hiring for.
How We’d Approach This
A clear, staged plan, not a black box
These are the service-specific steps inside our six-step process.
- 1
Map the AI system's attack surface (prompts, tool access, data sources, and integration points) before testing begins
- 2
Run adversarial red-team campaigns for prompt injection, jailbreaking, data exfiltration, and tool-use abuse specific to your deployment
- 3
Reproduce and document each successful exploit with a clear proof-of-concept so engineering can verify and fix it
- 4
Review remediations with your team and re-test the patched system to confirm the vulnerabilities are actually closed
What You Get
Deliverables from this engagement
- Full AI/LLM red-team findings report with reproducible exploit cases
- Risk-ranked vulnerability list with remediation recommendations
- Re-test verification confirming fixes close the identified gaps
- Attack surface map of the tested AI system for future reference
Six Ways We Could Architect This
Different engagement, different build, pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Read all 6 architectures as text
Lean Fast-Start Architecture
Scoping
- Target System Access Defined
- Attack Surface Mapped
- Test Scope Agreed
Testing
- Manual Prompt Injection Attempts
- Jailbreak Attempt Library
- Data Exfiltration Probe Tests
Findings
- Reproducible Attack Case Log
- Severity Triage
Delivery
- Findings Review Call
- Remediation Recommendations
- Final Red Team Report
- Retest Scheduled
Cloud-Native / Managed Services Architecture
Target Layer
- Client LLM API Endpoint
- Managed Test Harness Environment
- Cloud Sandbox Proxy
Attack Operations
- Automated Attack Payload Library
- Managed Logging And Tracing Service
- Response Capture Store
Analysis Layer
- Vulnerability Scoring Engine
- Findings Database
Delivery
- Client Facing Findings Dashboard
- Remediation Ticket Sync
- Retest Results Tracker
- Executive Risk Summary
Event-Driven & Automation-First Architecture
Triggers
- New Model Version Deployed
- Automated Regression Attack Suite Triggered
- New Jailbreak Technique Published
- Auto Added To Attack Library
Automation Layer
- Automated Prompt Injection Fuzzer
- Auto Captured Model Responses
- Auto Classified Vulnerability Type
Review Gate
- Critical Severity Detected
- Immediate Alert To Security Team
- Logged In Findings Backlog
Delivery
- Automated Findings Report Generated
- Slack Notification To Engineering
- Scheduled Weekly Retest Run
Enterprise-Grade & Compliance-Ready Architecture
Governance Layer
- Rules Of Engagement Signed
- Authorized Testing Scope
- Legal And Compliance Sign Off
Secure Testing
- Isolated Test Environment
- Role Based Tester Access
- Encrypted Findings Repository
Auditable Process
- Reproducible Attack Documentation
- Independent Peer Review
- Chain Of Custody Log
Compliance Delivery
- Audit Trail Export
- Redundant Evidence Backup
- Signed Off Red Team Report
- Mandated Retest Schedule
AI-Augmented, Human-in-the-Loop Architecture
Data Ingestion
- Target Model And System Prompts
- Known Attack Pattern Library
AI Analysis Layer
- AI Adversarial Prompt Generator
- Draft Attack Payloads
- Automated Execution Against Target
Human in the Loop
- Security Researcher Review
- Exploit Confirmed And Reproducible
- Flag False Positive To AI Generator
- Human Verified Vulnerability
Delivery
- Remediation Recommendation Drafted
- Client Security Team Notified
- Fix Verification Retest
- Closed Finding Logged
Integration-Heavy / Ecosystem-Connected Architecture
Client Systems
- Client LLM Application Stack
- Existing SIEM Platform
- Ticketing And Issue Tracker
Red Team Core
- Red Team Testing Engine
- Attack Simulation Results
- Vulnerability Findings Model
Two Way Sync Layer
- SIEM Alert Sync
- Issue Tracker Ticket Sync
- Security Operations Dashboard
- Engineering Backlog
Shared Governance
- Joint Review With CISO Office
- Published Security Posture Report
More in AI Strategy, Readiness & Governance
- AI Opportunity Discovery & Use-Case Prioritization
Facilitated workshops that surface the highest-ROI AI use cases across your business and rank them by impact and feasibility.
- AI Maturity & Readiness Assessment
A structured audit of your data, infrastructure, talent, and process readiness for AI adoption, with a scored gap report.
- AI Adoption Roadmap & Phased Rollout Planning
A sequenced, budget-aware plan for rolling out AI capability across teams without disrupting existing operations.
- Build vs. Buy vs. Partner Evaluation
Independent analysis of whether to build custom AI, buy a platform, or partner, based on total cost and strategic fit.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.
Talk to us about AI/LLM Security Red-TeamingMost engagements like this start as a $500–$2,500 pilot, see full pricing.