Your fine-tuned LLM for healthcare, finance, or legal services introduces novel attack surfaces. Generic security tools miss domain-specific jailbreaks, compliance violations, and specialized prompt injection techniques that could leak PHI, manipulate financial advice, or produce legally negligent outputs.
Service
Domain-Specific LLM Security Red Teaming
Tailored adversarial security testing for your custom, fine-tuned language models. We uncover domain-specific jailbreaks, compliance violations, and specialized prompt injection techniques that generic tools miss.
Tailored adversarial testing for custom, fine-tuned language models in high-stakes industries.
We simulate real-world adversaries to find vulnerabilities before they cause regulatory fines, reputational damage, or operational disruption.
- Industry-Specific Attack Simulation: We craft adversarial prompts using proprietary domain knowledge (e.g., obscure medical codes, financial regulations) to test for data leakage and harmful content generation.
- Compliance Violation Testing: Proactively test for breaches of HIPAA, GDPR, FINRA, or other frameworks through manipulated model outputs.
- Defense Validation: Receive actionable hardening guidance and benchmark against the MITRE ATLAS framework.
Move beyond generic scans. Secure the unique risks in your custom AI. Explore our broader AI Red Teaming and Adversarial Defense pillar or learn about protecting autonomous systems with AI Agent Goal Hijacking Defense.
GUARANTEED SECURITY IMPROVEMENTS
Tangible Outcomes of Our Red Teaming Service
Our domain-specific red teaming delivers measurable security hardening, directly reducing your AI's attack surface and compliance risk. We provide actionable reports, not just findings.
01
Identified Critical Vulnerabilities
We uncover and document exploitable security flaws in your custom LLM, including domain-specific jailbreaks, data leakage paths, and compliance violations, with proof-of-concept exploits.
15-30+
Critical Findings
MITRE ATLAS
Framework Mapped
02
Hardened Model Against Novel Attacks
Receive a security-hardened version of your model with mitigations implemented for discovered vulnerabilities, significantly raising the cost for real-world adversaries.
> 90%
Attack Surface Reduction
Remediation Guide
Included
03
Compliance Evidence for Audits
Generate defensible artifacts demonstrating due diligence for regulations like the EU AI Act, NIST AI RMF, and ISO/IEC 42001, turning security testing into a compliance asset.
EU AI Act
High-Risk Ready
Gap Analysis
Provided
05
Internal Team Upskilling
Your engineers and security staff gain hands-on understanding of AI-specific threats through our debrief sessions, building long-term internal defensive capabilities.
Knowledge Transfer
Session
Secure Coding
Best Practices
06
Foundation for Continuous Security
Our engagement establishes a baseline and repeatable testing methodology, enabling you to integrate AI red teaming into your SDLC and consider our Continuous AI Red Teaming Programs for ongoing protection.
Repeatable Process
Established
SDLC Integration
Blueprint
Comprehensive Security Assessment Tiers
Our Structured Testing Methodology
Our Domain-Specific LLM Security Red Teaming service is delivered through structured engagement tiers, each designed to match your model's criticality and compliance requirements. This table outlines the scope, deliverables, and support levels for each package.
| Security Assessment Component | Essential Audit | Comprehensive Red Team | Enterprise Resilience Program |
|---|---|---|---|
Initial Threat Modeling & Scoping | |||
Domain-Specific Jailbreak Testing (e.g., HIPAA, FINRA) | 50+ crafted attacks | 200+ crafted attacks | 500+ crafted & adaptive attacks |
Specialized Prompt Injection Testing | Core techniques | Advanced & chained techniques | Novel, research-grade techniques |
Compliance Violation Simulation (GDPR, EU AI Act) | Basic checks | Detailed scenario testing | Full adversarial compliance audit |
Adversarial Data Poisoning Assessment | |||
Model Extraction & Inversion Attack Testing | |||
Remediation Guidance & Technical Report | Summary report | Detailed report with PoC code | Prioritized roadmap & engineer briefing |
Retesting of Critical Vulnerabilities | 1 retest cycle | Quarterly retest cycles | |
Ongoing Threat Intelligence & Advisories | Monthly briefings & CVE monitoring | ||
Dedicated Security Engineer Support | Priority Slack Channel | Named Technical Account Manager | |
Typical Engagement Timeline | 2-3 weeks | 4-6 weeks | Ongoing program |
Starting Investment | From $15,000 | From $45,000 | Custom annual contract |
TAILORED ADVISORY
Core Capabilities of Our Red Team
Our red team combines deep adversarial expertise with your domain's specific risks. We don't just run generic tests; we simulate real-world, motivated attackers targeting the unique compliance, operational, and reputational vulnerabilities of your fine-tuned models.
01
Domain-Specific Jailbreak Testing
We engineer and execute sophisticated prompts designed to bypass your model's specialized safeguards, testing for compliance violations, data leakage, and harmful outputs unique to your industry's context and terminology.
1000+
Custom Jailbreak Vectors
MITRE ATLAS
Framework
02
Specialized Prompt Injection Attacks
Beyond basic injection, we test complex multi-step attacks that manipulate your model's reasoning chain, exploit its fine-tuned knowledge, and corrupt its outputs within high-stakes workflows like legal analysis or financial reporting.
Context-Aware
Attack Design
Multi-Vector
Testing Approach
03
Compliance & Regulatory Violation Simulation
We proactively test for scenarios where your model could violate HIPAA, FINRA, GDPR, or other critical regulations, identifying data handling flaws and output risks before they result in penalties or legal exposure.
HIPAA/GDPR
Focus
Proactive
Risk Identification
04
Adversarial Data Poisoning Assessment
We audit your training pipeline and fine-tuning datasets for vulnerabilities to poisoning attacks that could embed backdoors or bias, ensuring the integrity of your domain-specific model's foundational knowledge.
Supply Chain
Attack Surface
Pre-Deployment
Focus
05
Model Theft & Extraction Resistance Testing
We simulate advanced model extraction attacks to assess how easily a proprietary, fine-tuned model's weights or behavior can be stolen via API queries, protecting your significant R&D investment. Learn more about our broader Model Extraction and Inversion Attack Prevention services.
API Hardening
Focus
IP Protection
Outcome
06
Actionable, Developer-Focused Reporting
Receive clear, prioritized findings with reproducible attack code and direct remediation guidance your engineering team can implement immediately, reducing mean time to remediation (MTTR). This complements our ongoing Continuous AI Red Teaming Programs.
Prioritized
Remediation
Code Samples
Included
Tailored adversarial testing for high-stakes domains
Industry-Specific Testing Focus
Protecting Patient Safety and PHI Compliance
Secure clinical decision support and ambient AI against domain-specific threats. Our red teaming uncovers vulnerabilities in systems handling Protected Health Information (PHI) and medical logic, preventing compliance violations and protecting patient safety.
- HIPAA-Aligned Testing: Simulate attacks targeting PHI leakage through medical record summaries or diagnostic prompts.
- Clinical Logic Manipulation: Test for adversarial inputs that could corrupt treatment recommendations or drug interaction warnings.
- Medical Jailbreak Scenarios: Identify prompts that bypass safety guardrails to generate unverified or harmful medical advice.
- Integration Point Security: Assess risks where AI interfaces with EHRs like Epic or Cerner, a common vector for data exfiltration.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
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Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.
Enterprise searchRAGPermissions
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Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.
AI agentsWorkflow automationGovernance
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Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
AI integrationDecision supportModel routing
Read moreSecurity Testing for Custom Models
Frequently Asked Questions on LLM Red Teaming
Get answers to common questions about our tailored adversarial testing for fine-tuned language models in regulated industries.
A standard engagement takes 3-5 weeks from kickoff to final report. This includes 1-2 weeks for scoping and threat modeling, 2-3 weeks for active adversarial testing using frameworks like MITRE ATLAS, and 1 week for analysis and remediation guidance. For complex models with multiple specialized agents or extensive knowledge bases, timelines may extend to 6-8 weeks.
About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
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How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
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Pick the right approach
We define what needs search, automation, or product integration.
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Build the first useful version
We implement the part that proves the value first.
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Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
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