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AI Security Posture
Management.

Build an AI inventory that can be assessed against top risks and threats for AI usage, providing your organization with a complete security posture. A security posture is essential to understand the current state of AI adoption within your organization. With FireTail’s AI Security Posture Management solution, you gain full visibility into your AI usage, assess risks across models and agents, and safeguard your organisation from hidden threats.

Improve Your AI Security Posture

Identify, assess and remediate AI risks across your entire organization
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Complete
AI Visibility

Effective AI Security Posture Management is a key tool in enabling an organization to adopt AI in any meaningful way. Having a view on what you have, and the specific problems posed by each resource, app, or AI usage is key to understanding the risk of each AI instance.

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Total Control of AI Security

With single pane of glass visibility of all your AI usage, right across your entire organization, you can define and develop the policies needed to analyze what AI usage is acceptable, and what AI usage falls outside corporate governance boundaries.

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Maintain Compliance

Protect your organization from regulatory risks without stifling AI innovation. Many types of data are considered PII, or have compliance requirements like GDPR and CCPA associated with them. Lacking a security posture can put that compliance at risk.

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Cultivate Customer Trust

FireTail provides a clear, continuously updated view of your AI data flows and risk posture, helping you proactively communicate and demonstrate responsible data usage. Customer trust is not earned just once; it is maintained through visibility, accountability, and action.

“AI adoption was already happening across many parts of the organization. Our team had to get a quick understanding.”

App Security Director @ Asian MedTech

Get Started
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AI Security Posture Management (ASPM) for Enterprise AI

FireTail provides the tools needed to effectively identify and mitigate AI security risks.

Answering the question of AI adoption risk

Security leaders are often asked the question “What risks do we have?” with any technology platform. The growth rates, intense data usage and prevalence of shadow AI make AI a particular challenge. FireTail helps you answer that question with certainty.

FireTail dashboard showing the Inventory page with a grid of AI models including Command, Claude 3.5 Sonnet v2, Claude Instant, Nova Micro, and others.
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Inventory + Risk Assessment = Security Posture

FireTail combines a unique approach of a 3-tier analysis of AI risk:

  • Code analysis: FireTail performs static code analysis around all AI and LLM integrations, looking for common security best practices in coding and API driven integrations.
  • Log analysis: FireTail normalizes and analyzes logs from multiple LLM providers, looking for PII leakage, anomalies, guardrail invocations and more.
  • External LLM scanning (optional): Customers can opt in to have FireTail send intentionally malicious prompts to see whether your AI implementations are vulnerable to abuse.

Enabling safe and secure AI adoption

Having a strong and consistent AI security posture allows your organization to move forward with AI adoption, giving security leaders and business users peace of mind. Risks can be appropriately identified and managed.

Notification about medium risk detection of Personally Identifiable Information (PII) in AI logs, tagged as open and related to Claude 3.5 Sonnet.

How to Improve Your AI Security Posture

FireTail provides the tools needed to effectively identify and mitigate AI security risks.

Discover All AI Usage Across Your Organisation

Your AI posture starts with visibility. Identify every AI model, agent, data stream, integration, or shadow AI activity across your environment. Without a full inventory, unseen risks go unmanaged.

FireTail automatically scan and inventory all AI activity, from embedded LLMs to unchecked shadow AI, helping you build a complete map of your AI landscape.

FireTail integrations page showing options for setting up logging integrations including Google Cloud API Gateway, AWS API Gateway, AWS Bedrock, FireTail AppSync Lambda, FireTail Lambda Extension, AWS ALB, and Azure API Management Service.
FireTail API security dashboard showing total apps, AI models, APIs, endpoints, detected PII, and requests with graphs of API requests by apps and a world map of requests by location.

Assess AI and LLM Risks Continuously

Once you know where AI is being used, it’s critical to evaluate each asset. Look beyond static vulnerabilities and assess interactions, context, behaviour, and data exposures across your AI lifecycle.

  • Assessment should include:
    Prompt injection vulnerabilities
    Data leakage via logs or outputs
    Over-permissive API accesses
    Agent behaviour deviations
    Lack of guardrails or policy enforcement
  • Prioritise Remediation Based on Business Impact: Not all AI risks are equal. Risks affecting customer data, compliance, or critical systems should be dealt with first. Link risks to business context such as department, application, or regulatory exposure  to take smarter action.

    With FireTail: Risks are automatically ranked based on impact and linked with existing workflows.

Implement Governance, Monitoring, and Guardrails

A strong AI security posture isn’t just technical, it requires organisational governance. Define policies for AI usage, enforce role-based access, and monitor usage in production. Guardrails such as output filtering help prevent misuse and ensure safety.

FireTail's contextual governance engine aligns AI usage with business objectives, compliance needs, and operational boundaries

FireTail API Risk Dashboard showing a critical total risk score of 88.75 and a list of top APIs by risk score with details about findings, detected PII, requests, and endpoints.

Frequently Asked Questions About AI Security Posture Management

Find answers to common questions about protecting AI security posture management, APIs, and data pipelines using FireTail’s AI Security solutions

What is the difference between data security posture management and AI security posture management?

Data security posture focuses on data assets, how data is stored, accessed and protected. AI security posture covers the models, agents, prompts, integrations and data flows that power AI systems and ensures they are used safely and securely

What is an “AI agent posture management”?

This term refers to assessing the security, governance and operational risks specifically associated with autonomous or semi-autonomous AI agents operating within an organisation. It’s increasingly relevant as organisations deploy AI bots, assistants and agents.

How does FireTail help with AI governance and strategic visibility?

Our platform links AI‐usage metadata to your organisational context, mapping usage to business units, functions, regulatory domains and risk profiles, enabling strategic visibility and governance oversight.

Discover your AI exposure now

Start a free trial of FireTail today and get 14 days to discover AI usage right across your entire organization.