Primary Purpose
Continuously assess and improve the security posture of enterprise AI systems and their supporting data.
Enterprise AI Security
What Is AI Security Posture Management?
AI Security Posture Management, or AI-SPM, is the continuous process of discovering AI assets, identifying data and access risk, evaluating security controls, monitoring AI activity, and remediating weaknesses across the enterprise AI lifecycle.
Discover AI assets
Assess data and access risk
Continuously improve AI posture
AI Security Posture Lifecycle
01
Discover AI Assets
Inventory models, agents, prompts, datasets, pipelines, and tools
Discover
02
Map Data and Access
Connect AI systems to sensitive data, identities, permissions, and lineage
Map
03
Assess AI Risk
Prioritize vulnerabilities, exposure, misuse, and policy violations
Assess
04
Enforce and Remediate
Apply controls, reduce exposure, and continuously improve posture
Protect
Models
Agents
Prompts
Data
Identities
Tools
Quick Definition
AI Security Posture Management at a Glance
AI-SPM gives security and governance teams continuous visibility into AI assets, the data they use, the identities that access them, and the security weaknesses that create enterprise risk.
AI Assets Covered
Models, agents, copilots, prompts, datasets, vector databases, pipelines, applications, and connected tools.
Risk Context
Data sensitivity, ownership, access, permissions, lineage, usage, exposure, vulnerabilities, and policy violations.
Common Risks
Shadow AI, sensitive data exposure, excessive agent access, prompt injection, insecure pipelines, and ungoverned AI use.
Key Stakeholders
Security, AI governance, data, privacy, risk, compliance, model, engineering, and identity teams.
Continuous Activity
AI-SPM continuously discovers, assesses, monitors, prioritizes, enforces, remediates, and reports.
Core Definition
What Is AI Security Posture Management?
AI Security Posture Management is a cybersecurity discipline that continuously identifies, evaluates, prioritizes, and reduces security risk across enterprise AI systems and the data, identities, infrastructure, and tools that support them.
AI-SPM begins by creating an inventory of AI models, agents, copilots, applications, prompts, datasets, vector databases, pipelines, APIs, and third-party AI services.
It then connects these assets to security context such as sensitive data, lineage, ownership, access permissions, non-human identities, vulnerabilities, usage, exposure, and applicable policies.
This context helps teams identify high-risk conditions, including sensitive training data, exposed vector stores, over-privileged agents, insecure model connections, unapproved AI tools, and unmonitored prompt activity.
AI-SPM extends posture management into AI-specific environments where traditional cloud, application, and data security controls may not provide sufficient visibility.
Related Terminology
AI Asset Inventory
A continuously maintained record of models, agents, datasets, prompts, tools, pipelines, owners, purposes, and environments.
AI Risk Management
The process of identifying, assessing, treating, monitoring, and documenting risks created by AI systems.
AI TRiSM
A framework for managing AI trust, risk, security, governance, reliability, explainability, and compliance.
Shadow AI
AI tools, models, agents, or workflows used without formal approval, visibility, ownership, or governance.
Key Differences
AI-SPM vs. Related Security Practices
AI-SPM complements data, cloud, application, and model security by connecting AI-specific assets to the data, identities, access, usage, and risks behind them.
AI-SPM
Where does risk exist across enterprise AI?
Discovers AI assets and evaluates data, identities, permissions, vulnerabilities, usage, exposure, controls, and policy violations.
DSPM
Where is sensitive enterprise data exposed or over-accessible?
Discovers and classifies sensitive data, then identifies excessive access, exposure, toxic combinations, and data policy violations.
CSPM
Are cloud resources configured securely?
Identifies cloud misconfigurations, exposed resources, compliance drift, insecure infrastructure, and cloud policy violations.
Model Security
Is an individual AI model resilient against attack or manipulation?
Focuses on risks such as adversarial inputs, model theft, poisoning, evasion, extraction, unsafe behavior, and integrity compromise.
AI Security Lifecycle
How AI Security Posture Management Works
AI-SPM creates a continuous security cycle that moves from AI discovery and data mapping to risk prioritization, policy enforcement, remediation, and evidence.
Discover
Inventory AI Assets
Identify sanctioned and shadow AI models, agents, copilots, prompts, applications, datasets, vector stores, pipelines, APIs, and third-party services.
Map
Connect AI to Data and Identity
Map sensitive data, lineage, owners, human and non-human identities, roles, credentials, permissions, tools, and downstream systems.
Assess
Evaluate AI Risk
Assess vulnerabilities, overexposure, excessive access, insecure integrations, sensitive prompts, unapproved use, and policy violations.
Prioritize
Rank Risk by Business Impact
Prioritize findings using data sensitivity, exploitability, exposure, access, usage, lineage, ownership, and regulatory impact.
Enforce
Apply Security Policies
Enforce controls for AI access, agent permissions, prompt content, response handling, data use, model connections, and approvals.
Remediate
Reduce AI Exposure
Restrict access, remove sensitive data, correct configurations, isolate risky assets, update controls, and route remediation to owners.
Monitor
Continuously Validate Posture
Monitor AI activity, data access, agent behavior, changes, violations, remediation progress, and control effectiveness.
AI Risk Exposure
Common AI Security Posture Risks
AI environments combine sensitive data, powerful models, machine identities, external services, and autonomous actions, creating risks that span traditional security boundaries.
Shadow AI
Unapproved AI tools, models, agents, or copilots may process enterprise data outside established security and governance controls.
Sensitive AI Data
Training, tuning, retrieval, prompt, and inference workflows may expose personal, regulated, confidential, or proprietary data.
Excessive Agent Access
AI agents may receive broad credentials, permissions, tools, or data access that exceed their approved business purpose.
Prompt Injection
Malicious instructions may manipulate models or agents into ignoring policies, revealing data, or misusing connected tools.
Insecure AI Pipelines
Weak access controls, untrusted datasets, exposed vector stores, and vulnerable integrations can compromise AI workflows.
Limited AI Observability
Incomplete logs and disconnected controls can obscure which data AI accessed, what actions it took, and why.
Enterprise AI Resilience
Why AI Security Posture Management Matters
AI adoption can outpace existing security processes. AI-SPM helps organizations replace fragmented AI visibility with continuous, risk-based security oversight.
Discover Unmanaged AI
Identify shadow AI systems, unsanctioned tools, unknown agents, and unregistered datasets operating outside approved processes.
Protect Sensitive AI Data
Find regulated and confidential data used across training, retrieval, prompting, inference, and agent workflows.
Govern AI Access
Understand which users, service accounts, agents, applications, and tools can access AI systems and their underlying data.
Prioritize AI Risk
Rank findings using data sensitivity, access, exposure, usage, business impact, and control effectiveness.
Enforce AI Policies
Translate security and governance requirements into controls for data use, prompts, access, actions, retention, and remediation.
Prove AI Control
Maintain evidence of AI inventory, ownership, risk, access, policy enforcement, remediation, and continuous monitoring.
Secure Enterprise AI
AI Security Posture Management Best Practices
Effective AI-SPM combines AI asset visibility, data intelligence, identity context, policy controls, continuous monitoring, and risk-based remediation.
Maintain a Complete AI Inventory
Continuously identify AI models, agents, copilots, prompts, datasets, vector stores, pipelines, APIs, owners, and business purposes.
Connect AI Assets to Sensitive Data
Map the personal, regulated, confidential, proprietary, and toxic data used across AI training, retrieval, prompting, and inference.
Govern Human and Non-Human Access
Identify users, agents, applications, service accounts, credentials, tokens, roles, and delegated permissions connected to AI.
Prioritize Risk With Context
Rank security findings using data sensitivity, exposure, access, usage, lineage, ownership, exploitability, and business impact.
Enforce Controls at the Data Layer
Apply policies to sensitive data before it enters models, prompts, vector databases, agents, or downstream AI workflows.
Continuously Monitor and Remediate
Monitor posture changes, access, agent activity, policy violations, new AI assets, and remediation progress over time.
Secure Enterprise AI
AI Security Posture Management Best Practices
Effective AI-SPM combines AI asset visibility, data intelligence, identity context, policy controls, continuous monitoring, and risk-based remediation.
Maintain a Complete AI Inventory
Continuously identify AI models, agents, copilots, prompts, datasets, vector stores, pipelines, APIs, owners, and business purposes.
Connect AI Assets to Sensitive Data
Map the personal, regulated, confidential, proprietary, and toxic data used across AI training, retrieval, prompting, and inference.
Govern Human and Non-Human Access
Identify users, agents, applications, service accounts, credentials, tokens, roles, and delegated permissions connected to AI.
Prioritize Risk With Context
Rank security findings using data sensitivity, exposure, access, usage, lineage, ownership, exploitability, and business impact.
Enforce Controls at the Data Layer
Apply policies to sensitive data before it enters models, prompts, vector databases, agents, or downstream AI workflows.
Continuously Monitor and Remediate
Monitor posture changes, access, agent activity, policy violations, new AI assets, and remediation progress over time.
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See and Reduce Risk Across Enterprise AI
BigID helps organizations discover AI assets, map sensitive data, assess AI security posture, govern agent access, enforce policies, monitor activity, and automate remediation.
AI Security Posture
AI-SPM
Assets • Data • Access • Risk
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Assess
Remediate
Monitor
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