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SECURING YOUR AI JOURNEY

Enable AI-Led Growth
Without Expanding Enterprise Risk

AI doesn’t just increase productivity. It concentrates privilege, expands attack surface, and automates risk. If your AI systems are secured the same way as legacy software,  you are blind to the most dangerous behaviors.

UltraViolet Cyber provides security services across the AI lifecycle, combining strategy, threat modeling, adversarial testing, monitoring, and training to support secure AI adoption.
SIEM Health Check

Is Your SIEM Actually
Detecting Threats?

Most teams assume their SIEM is working. Our practitioners routinely find that roughly 40% of active detection rules are stale, duplicated, or haven’t fired in 90 days — and that critical log sources were quietly dropped to manage licensing costs. Our SIEM Health Check tells you exactly what you’re missing.

UVC_focus-on-outcomes

The Enterprise AI Risk Shift

AI introduces a distinct operational risk profile embedded directly into enterprise systems, data pipelines, and decision flows. As models, agents, and automation scale across the organization, security must operate continuously and in alignment with how AI behaves in production environments.

 

Where Risk Is Emerging

AI Agents & Autonomous Workflows
  • Privileged API chaining

  • Goal hijacking and unintended execution

  • Prompt injection attacks

  • Lateral movement through AI integrations

  • Data leakage via workflow automation

AI Infrastructure & Model Expansion
  • Model theft and IP exfiltration

  • GPU and compute targeting

  • Supply-chain compromise of third-party models

  • Data poisoning and model manipulation

AI-Enabled Products & Customer Features
  • Hallucinated outputs influencing business decisions

  • Exposure of regulated or sensitive customer data

  • Abuse of generative interfaces

  • Regulatory scrutiny over automated outcomes

Five Signs Your SIEM Needs a Health Check

1. Your licensing bill keeps climbing — and log coverage keeps shrinking

Legacy SIEMs charge by data volume. As cloud, SaaS, and ephemeral workloads grow, the bill scales linearly. Teams are forced to choose: pay more, or drop log sources and create blind spots.

2. Alert volume is high. Detection fidelity is not.

Static correlation rules generate floods of false positives. Analysts spend hours chasing disconnected alerts instead of investigating real threats.

3. Cloud, SaaS, and identity coverage is assumed — not verified

Your SIEM was built before multi-cloud was default. Coverage of AWS, Azure, GCP, Okta, M365, and SaaS platforms is often shallow, inconsistent, or relies on manual connector work that breaks silently.

4. Engineering talent is consumed by maintenance, not detection

Custom parsers, regex tuning, infrastructure management, server upgrade cycles. When your team spends more than 20% of capacity keeping the SIEM running instead of building detections and hunting adversaries, the platform is working against you.

5. Response is fully manual — detect to contain takes dayss

Older SIEMs alert but cannot act. No automated timelines, no integrated playbooks, no connection to ticketing or response tooling. Every containment action — isolating a host, revoking credentials — requires multiple manual steps across multiple tools. MTTR stays high, and leadership keeps asking why.

Built for Security Practitioners
Who Run SIEM Environments

The SIEM Health Check is a practitioner-to-practitioner working session. It’s for the people who actually operate detection infrastructure, manage analyst workflows, and own security outcomes day to day.

Your analysts are triaging alerts, not hunting threats

When tier-1 spends 30+ minutes manually stitching logs to understand a single alert — or when high-priority events get deprioritized because the queue is overwhelming — you have a structural detection problem. The Health Check surfaces exactly where the signal-to-noise ratio breaks down and how to fix it without sacrificing coverage.

You suspect coverage gaps you can’t fully map

Cloud workloads, SaaS platforms, and identity sources often look covered but aren’t. If data sources have been deprioritized to control licensing costs, or detection content hasn’t been formally tuned in over a year, you have blind spots. We map them against your actual environment and MITRE ATT&CK — not assumed coverage.

Renewal is approaching and you need a credible baseline

If your contract renews within 18 months and leadership needs to decide between renewing, optimizing, or migrating, a Health Check gives you the evidence to make that case — cost model, coverage gaps, migration readiness, and a path forward you can defend to your CISO or board.

Maintenance is consuming your best engineers

 When more than 20% of your engineering capacity goes to writing parsers, tuning rules, and managing SIEM infrastructure rather than building detections, the platform is working against your team. We quantify that cost and identify where automation or architecture changes would reclaim it.

You’re not sure your SIEM delivers what was promised

Most teams have never done a formal review of whether their SIEM delivers on the original business case. If you’re choosing which log sources to ingest based on cost rather than risk — or you can’t confidently answer “what would we miss if this went dark?” — the Health Check is the answer.

The UltraViolet AI Security Framework

We secure your AI journey across eight foundational domains.

  • 01 Strategy & Governance Define how AI is used, owned, and controlled.
  • 02 Risk Management Identify and mitigate risks unique to AI systems.
  • 03 Data Security & Privacy Protect training and inference data.
  • 04 Model Security & Integrity Prevent tampering, poisoning, and theft.
  • 05 Application Security Extend secure SDLC to AI-enabled components.
  • 06 Monitoring & Detection Detect AI misuse, anomalies, and drift.
  • 07 Compliance & Regulatory Alignment Prepare for emerging AI regulatory requirements.
  • 08 Awareness & Training Build an organization that uses AI safely and effectively.

Unlike siloed providers, we connect offensive validation with continuous defense — creating a closed feedback loop between testing and monitoring.

Enterprise AI Initiatives and Expected Security Outcomes

AI adoption typically shows up in a consistent set of enterprise initiatives. Each one benefits from clear security outcomes that keep innovation moving.

1. Enterprise AI Agents for Automation and Decision Support
Common exposure

Privileged access abuse, data leakage, unintended actions.

How UV helps

AI penetration testing and adversarial evaluation to identify security gaps across models, APIs, and workflows.

2. AI-Enabled Cloud Migration and Modernization
Common exposure

Expanded attack surface, misconfigurations, inconsistent controls across environments.

How UV helps

Validate AI pipelines and cloud integrations through continuous testing and targeted assessments.

3. AI Infrastructure Expansion (AI Compute, Data Centers, and Platforms)
Common exposure

High-value infrastructure targeted for IP theft, supply-chain compromise, and disruption of critical compute resources.

How UV helps

Continuous monitoring of AI platforms to detect and investigate anomalies, plus risk-informed hardening guidance.

4. Embedding AI into Core Products
Common exposure

Model manipulation, data poisoning, and regulatory exposure as AI impacts business outcomes.

How UV helps

Adversarial model evaluation to understand behavior under malicious inputs and corrupted data, paired with governance and controls.

5. AI-Driven Productivity and Customer-Facing Features
Common exposure

Customer data exposure, prompt injection abuse, and reputational risk from AI-generated errors or misuse.

How UV helps

Test AI-enabled applications and monitor production signals to detect misuse patterns and runtime anomalies.

Built by Operators.
Designed for Production.

AI security is defined in production environments where models, agents, and automation interact with live systems and data. UltraViolet brings operational rigor, adversarial depth, and continuous monitoring to ensure those systems perform securely at scale.

Why UltraViolet Cyber?

  • 01 Built by Operators Founded by former U.S. intelligence community operators, UltraViolet brings offensive DNA to defensive strategy. We don’t just know how to detect threats, we know how attackers think.
  • 02 Flexible Engagement Models Whether co-managed, fully outsourced, or embedded, we adapt to your team, your tech stack, and your mission.
  • 03 Federal-Grade Operational Rigor Trusted by DHS and Fortune 500 enterprises alike, UltraViolet delivers operational rigor with agile execution.
  • 04 Unified Red, Blue, and Purple Operations
    UltraViolet operates offensive, defensive, and purple team capabilities as a unified model, creating tighter coordination across testing, detection, and response.
  • 05 Compliance-Driven Assurance
    UltraViolet helps organizations meet audit, regulatory, and customer assurance requirements while strengthening security in practice across testing, monitoring, and governance.

 

Built by Operators.
Designed for Production.

AI security is defined in production environments where models, agents, and automation interact with live systems and data. UltraViolet brings operational rigor, adversarial depth, and continuous monitoring to ensure those systems perform securely at scale.

Red Team Adversarial Simulation
Blue Team 24x7 Monitoring
Purple Team Continuous Validation
Federal-Grade Operational Rigor
Vendor-Agnostic SOC Integration

Start With a SIEM Health Check

A senior UltraViolet practitioner will review your submission and reach out within one business day to schedule. This is a working session with someone who builds and operates SIEMs at enterprise scale.

  • Verified inventory of what data is actually being ingested — confirmed vs. assumed coverage

  • Full review of which detections are active, stale, duplicated, or generating noise with no value

  • Honest assessment of detection signal quality and analyst alert burden

  • Architecture review covering data flows, coverage gaps, and operational design

  • Findings playback from a senior practitioner with a recommended path forward