Service
Architecture review before implementation
Implementation scope and rollout planning
Clear next-step recommendation
Proactive security testing to harden your mission-critical AI models against novel attacks.
Deploy AI with confidence. Our adversarial red teaming identifies vulnerabilities in your models before they can be exploited, protecting your operations and intellectual property.
We conduct systematic security assessments using frameworks like MITRE ATLAS to simulate real-world attacks, including:
Our service delivers a detailed threat report with prioritized remediation steps, moving you from reactive patching to proactive defense. We benchmark your system's resilience and provide actionable guidance to implement robust countermeasures.
Key Deliverables:
This service is part of our broader Defense and National Intelligence AI pillar, which includes secure development for contested environments. For foundational security governance, explore our Enterprise AI Governance and Compliance Frameworks service.
We provide concrete, measurable security improvements for your mission-critical AI systems. Our service is built on the MITRE ATLAS framework and delivers verified outcomes, not just theoretical assessments.
Your AI models are systematically hardened against known attack vectors like data poisoning, evasion, and prompt injection. We deliver a security-certified model artifact with a detailed threat matrix, enabling deployment with confidence in contested environments.
Receive a comprehensive, actionable report detailing your AI system's vulnerabilities, prioritized by exploitability and potential mission impact. This includes specific remediation steps and code-level fixes, not just high-level findings.
Move beyond a point-in-time audit. We establish a continuous adversarial testing program, simulating novel attack techniques and monitoring for model drift or new vulnerabilities, ensuring your defenses evolve with the threat landscape.
We design and implement a resilient MLOps pipeline with built-in adversarial detection layers, secure model serving, and automated rollback capabilities. This ensures operational integrity even under active attack conditions.
Your engineering and security teams gain hands-on experience through tailored adversarial AI war-gaming exercises. We transfer knowledge on attack methodologies and defensive countermeasures, building internal expertise.
Our service delivers the evidence and documentation required for compliance with frameworks like NIST AI RMF, ISO/IEC 42001, and upcoming EU AI Act mandates for high-risk systems. Achieve audit readiness for national security contracts.
Choose the level of adversarial testing and defense hardening required for your operational AI systems, from foundational assessments to continuous resilience programs.
| Security Capability | Foundational Audit | Comprehensive Red Team | Continuous Resilience Program |
|---|---|---|---|
MITRE ATLAS Framework Assessment | |||
Adversarial Attack Simulation (Data Poisoning, Evasion) | Basic Scenarios | Full Spectrum | Full Spectrum + Novel Research |
Prompt Injection & Jailbreak Testing | Standard Templates | Custom, Multi-Vector Attacks | Custom + Automated Fuzzing |
Model Inversion & Membership Inference Tests | |||
Supply Chain & Training Data Integrity Audit | |||
Remediation Roadmap & Hardening Guidance | High-Level Report | Detailed, Actionable Plan | Plan + Implementation Support |
Continuous Monitoring & Drift Detection | |||
Quarterly Adversarial Updates & Re-Testing | Optional Add-on | ||
Dedicated Security Engineer Support | Priority Slack Channel | Dedicated Engineer + On-Call | |
Typical Engagement Scope | Single Model / Use Case | Portfolio of Critical Models | Enterprise-Wide AI Security Posture |
Starting Investment | $25K - $50K | $75K - $150K | Custom (Contact for Quote) |
Our adversarial defense and red teaming services harden your operational AI against novel attack vectors, ensuring resilience in contested environments. We deliver verifiable security postures for models processing classified intelligence, autonomous systems, and secure communications.
We conduct systematic security assessments using the MITRE ATLAS framework to identify vulnerabilities in your AI systems, including data poisoning, model evasion, and prompt injection attacks specific to defense applications.
We implement defensive techniques like adversarial training, input sanitization, and ensemble methods to fortify your mission-critical models against manipulation, ensuring reliable performance under attack.
Move beyond one-time audits with our ongoing red teaming program. We simulate advanced persistent threats (APTs) to continuously probe your AI deployment, providing real-time alerts and mitigation strategies.
We integrate security-first practices into your entire MLOps pipeline—from secure data curation and model training to hardened deployment and monitoring—ensuring governance and compliance from inception.
We specialize in securing complex AI agent networks and multi-agent systems against novel threats like goal hijacking and inter-agent manipulation, which are critical for autonomous planning and logistics. Learn more about our Multiagent Systems (MAS) Architecture.
Protect sensitive model weights and inference data with hardware-based Trusted Execution Environments (TEEs). We deploy AI within encrypted memory enclaves, securing data in use for the most classified workloads. Explore our Confidential Computing for AI Workloads service.
Proactively harden mission-critical AI systems against novel attack vectors with adversarial testing and resilient defense engineering.
We conduct continuous adversarial testing using frameworks like MITRE ATLAS to identify and remediate vulnerabilities before adversaries can exploit them. Our red teaming services simulate real-world attacks, including:
We build AI systems that are not just accurate, but provably resilient in contested environments.
Our defense engineering integrates hardened MLOps pipelines, secure model deployment on edge devices, and continuous monitoring for performance drift and adversarial manipulation, ensuring operational integrity under pressure.
This service is a core component of our broader Defense and National Intelligence AI offerings, which also include Secure Federated Learning for Defense and Resilient AI for Contested Environments.
Enabling Efficiency, Speed & Accuracy
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Common questions about our specialized security service to harden operational AI systems against novel attack vectors like data poisoning, model evasion, and prompt injection.
We follow a structured, intelligence-led approach based on the MITRE ATLAS framework. Our process begins with threat modeling specific to your model's architecture and operational context. We then execute a multi-phase engagement covering data poisoning, model evasion, extraction, and integrity attacks, culminating in a detailed report with prioritized, actionable remediation steps. This methodology is proven across 50+ mission-critical AI systems.
About the author
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.
How We Work
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.
The first call is a practical review of your use case and the right next step.
