Widespread enterprise adoption of AI has created a pressing need for security solutions — a tall order given that AI’s reach into organizational infrastructure and data is enormous and continues to grow.
Moreover, where an organization sits on the AI maturity curve impacts its security needs. Trail of Bits CEO Dan Guide describes the AI journey as a migration from AI-assisted, where AI tools are used on existing workflows; through AI-augmented, which uses new workflows based on AI; to the AI-native organization, where AI “becomes a core participant in the delivery and operations of a business.”
Those three stages require very different approaches to securing AI. They also present challenges for AI security vendors, whose platforms must fit in multiple places in a corporate network and interact with a broad spectrum of applications — especially as agentic AI expands. As analyst David Linthicum recently posted, “the conversation now has to shift from model fascination to operational discipline. The question is how those agents should be governed once they begin touching workflows that affect customers, employees, suppliers, compliance, and revenue.”
Making matters worse is that the average enterprise manages 37 agents, with more than half running without security oversight or logging, according to Microsoft’s 2026 Cyber Pulse report, which also found that, while 80% of Fortune 500 companies use active AI agents, only 10% have a clear strategy for managing them.
That lack of strategy also opens the door for attackers to abuse corporate AI systems for malicious purposes, as the recent exploit of Meta’s account recovery using chatbots demonstrated.
The trick to securing AI systems is in understanding how much protection is needed and where it should be applied in the expanding AI universe. While one could rent a well-meaning AI agent called Sentry for $7,400 per month to automate the daily work of a SOC analyst, many organizations rolling out AI across their business would be best served by considering AI security posture management (AI-SPM) tools.
Over the past two years, this emerging field has matured, with many security vendors incorporating or acquiring SPM features as part of their general security product portfolio.
Some vendors, such as SentinelOne and Concentric, don’t specifically sell AI-SPM per se, but offer an SPM tool that is part of a larger package of AI security services. Others offer AI-SPM in conjunction with their other SPM tools or CNAPP security offerings. Some vendors, such as Cyera and Palo Alto, offer multiple AI-SPM packaging alternatives with differing feature sets.
Choosing the right product requires careful examination of the roster of features and integrations each product offers to ensure that it doesn’t duplicate existing security tooling or worse, leave important coverage gaps.
Here we take a deeper look at the AI-SPM product category, with a breakdown of offerings from 14 of the leading vendors in this increasingly important security ecosystem.
AI security posture management explained
AI security posture management is an evolving cybersecurity discipline focused on ensuring the integrity and security of AI and machine learning systems. AI-SPM encompasses strategies, tools, and techniques for monitoring, assessing, and enhancing the security of AI models, data, pipelines, applications, and services, even as threats to those entities continually evolve.
In the past, security posture management tools were designed for two situations: to protect general cloud operations against misconfigurations and abuse, which is the province of cloud security posture management tools; and to protect against data leakage or malware infections, which is the province of data security posture management tools. With the rise of AI and large language models (LLMs), a third SPM product category is needed to check AI cloud services and their SDKs (like Hugging Face Transformers or Azure Open AI SDK) to prevent model abuses. This is because numerous studies have documented how AI training data can be the subject of an attack or how bad data can be injected into models to manipulate results, including creating malicious backdoors for attackers to use to enter your enterprise.
The latest reports about attacks on AI and AI abuse can help you better understand the scope of security challenges rapidly evolving today. MITRE continues to enhance its comprehensive database of adversary tactics — Adversarial Threat Landscape for Artificial-Intelligence Systems (ATLAS) — based on real-world attack observations. ATLAS currently spans 170 techniques and 57 case studies. MIT researchers also maintain a growing database of more than 1,700 AI-related risks that they have observed from various AI sources. Another great source of AI-related attack methods is from the Open Worldwide Application Security Project (OWASP), which maintains a Top 10 list of LLM exploits. Security managers should examine them before choosing any AI-SPM product. They should also consult Richard Stiennon’s Guardians of the Machine Age, the most comprehensive collection of general security vendors, listing more than 100 AI security vendors. The printed book offers a deeper dive into the specifics of these tools.
The AI-SPM vendor landscape is quickly evolving, as incumbent security vendors have made numerous acquisitions. Palo Alto Networks bought Protect.ai last year; Cato Networks acquired Aim.security; Orca acquired Opus for AI agentic security; SentinelOne acquired Prompt.Security; Varonis acquired a variety of companies, including Cyral, SlashNext, and AllTrue.ai; and Google acquired Wiz.
Why enterprises need AI-SPM
AI-SPMs have been designed to protect enterprise networks and applications from a range of threats to AI systems. Just like no modern business would assemble a network without an appropriate firewall, AI-SPMs “ensure that AI models stay explainable, fair, accountable, transparent and equitable,” Forrester analyst Andras Cser tells CSO. “Further good security hygiene dictates that AI infrastructure should not be allowed to be used as a steppingstone for hackers for lateral movement and data exfiltration, and should include policies to prevent and fix configuration drift.”
AI-SPM can also help organizations standardize on a series of AI policies, procedures, tools, and workflows that can boost their security. Guido’s talk — linked above — is chock full of suggestions on how Trail of Bits accomplished this.
Major AI-SPM trends and product features
All AI-SPM vendors make use of agentless configurations, accessing cloud-based models and leaving data on their existing platforms. This is both a security measure and to avoid moving the massive data repositories involved across the internet.
AI-SPM vendors also make use of AI-related mechanisms to classify and track these vast data collections and to protect them against potential abuse and attack. Many have integrated their AI-SPM solutions in one of three directions:
Bolting AI-SPM onto their existing cloud or data SPM platforms with rules, compliance checking, best practices, and protection policies that bridge all three types of security postures.
Stitching AI-SPM into their general AI security product that can be used to formulate AI-specific policies and perform AI-based red team and penetration testing in an effort to protect AI pipelines and workloads and uncover ways that shared AI services and platforms could be compromised.
Incorporating AI-SPM to help identify sensitive data referenced by an AI model and to examine training data exposed to a third-party or external application.
Some vendors, especially established security vendors such as CrowdStrike, Proofpoint, Palo Alto, Varonis, and Wiz, have hundreds of third-party integrations that cover the AI waterfront (such as AI assistants and model suppliers) and general IT security arena (such as development pipelines, data feeds, and tools such as SOAR and SIEM). All three types of integrations can provide better guiderails and limit an AI’s blast radius.
But AI-SPM is still evolving. Some vendors’ tools just perform a top-level inspection of one or two services from each of the big three cloud platforms’ AI services (Amazon, for example, has dozens of AI-related service offerings), whereas others (such as Palo Alto Networks, Cato, Cyera, Varonis, and Wiz) take a deeper dive, performing a more comprehensive examination of AI data from the AI vendors themselves and other model sources.
There are two open source efforts as well: Orca’s GOAT is a free learning platform that is based on the OWASP top 10 risks. Palo Alto’s Protect.ai has its collection of open-source tools on GitHub for scanning models and discovering AI interactions and automated red teaming called ProtectAI OSS. However, neither of these projects has been recently updated.
How to choose an AI-SPM tool
Here are several considerations when deciding on the best AI-SPM tool for your enterprise:
Does the vendor work with your existing security tool collection? This has two dimensions: integrating with other SPM products (such as data or cloud protection), and integrating with third-party tools such as SOARs, SIEMs, or DLP products. We have included some vendors that don’t have a specific AI-related SPM (such as Concentric and CrowdStrike) but have deeply embedded AI protection into their platforms.
How deep is the coverage across the cloud platform providers? The big three (AWS, Azure, and GCP) have many services that touch various aspects of AI, and some products only work with a few of them, or only connect with PaaS security “hubs.”
Does the vendor continuously scan your infrastructure looking for vulnerabilities? AI can be quickly adopted and is very dynamic, so discrete scans are less useful.
How important is having a tool that can help with AI red teaming? Understanding the dynamic nature of how AI operates means having a different approach to penetration testing, and this can be a very useful feature. Only a few vendors offer this feature (such as Concentric, Palo Alto Networks, and Varonis).
Leading AI-SPM vendors and products
We reached out to a range of leading AI-SPM security vendors to demonstrate their AI-related tools. Below are more details about each of the 14 we had the opportunity to preview. We have also summarized each vendor’s offerings in the features table, which also provides links, when available, to pricing and third-party integration details. Several vendors didn’t respond to our inquiries, including Baffle.io, Invicti, SecurityCompass, Tonic Security, and Zscaler.
Arthur.ai
Arthur.ai’s platform is a single product that offers deep PaaS coverage with both AWS and Google Cloud Platform, although unlike other AI-SPMs it doesn’t offer a wide range of third-party integrations. It includes application runtime security protection. It also scans network traffic continuously and watches for agent activity, along with policy guardrails to protect against prompt injection and sensitive data leakage. It includes behavioral analytics and governance that catch abusive agentic activities. There are free and paid versions starting at $10,000 annual plans for smaller networks.
Cato Networks AI Security for End Users
Cato Networks AI Security for End Users is one of three separate AI security packages that work together with Cato’s SASE platform, the other two being protection for applications (both runtime and across the software development lifecycle) and for real-time agentic operations. The three AI packages are meant to be purchased together to provide audit trails showing what users are doing with their AI tools and to help understand and illustrate the risks. Cato’s tools can also prevent prompt injection and data leaks and find compliance blind spots. Its platform has a wide collection of third-party integrations, including CrowdStrike, Microsoft, and Splunk SIEMs, and various data sources such as Google’s Chronicle and Rapid7. Cato Networks did not reveal pricing.
Concentric AI and Data Security Governance
Concentric sells a DSPM platform labelled “AI and Data Security Governance.” There is no specific AI tool, although AI pervades its product in a variety of places, including scanning various models for prompt injection, automated remediation, and the discovery and classification of data flows. It offers a wide collection of third-party integrations. On the AWS Marketplace, it sells an entry-level version for $50,000 per year that covers up to 25TB of data, with higher fees for larger data collections.
CrowdStrike Falcon AI-SPM
CrowdStrike Falcon AI-SPM is not a separate product, but part of the overall Falcon Cloud security platform. It can correlate risk findings with other security services monitored by the full Falcon platform. It includes discovery of AI services and models across a variety of cloud platforms, including containers and virtual images, and can detect misconfigurations and dependencies with other software. It scans OpenAI, Amazon Bedrock, Amazon SageMaker, and Vertex AI models. Falcon has more than 250 integrations available to a wide collection of third-party security tools. You can request a free 15-day trial, but no further pricing information was disclosed.
Cyera AI Guardian
Cyera.io specializes in data file level classification. It packages its AI-SPM product in two separate bundles: either with its flagship DSPM product that has added what you might think of as AI-enriched data link protection as part of the default product’s features, or with a more complete set of security features called AI Guardian. Cyera also offers a specialized add-on module used for Microsoft Copilot data scanning that can detect data used by insiders, for example. Cyera’s AWS Marketplace pricing can be found here and starts at $50,000 per year.
Guardrail Technologies Traffic Light for Code and AI
Guardrail Technologies Traffic Light for Code and AI is designed to be a simple way to flag potential AI abuse by scanning AI-generated code and returning a red/yellow/green result to indicate potential for compromise. There is no remediation, but the tool integrates across the major AI vendors, including Anthropic, Azure Open AI, Hugging Face, and AWS Bedrock, and general security tools such as Wiz and Snyk. Guardrail has a custom AI security consulting business as well called AI Guardian. Very transparent pricing page and a 60-day free trial is available.
Microsoft Purview
Microsoft has bundled its various security posture tools into its Purview offering, which includes a series of AI-based Copilot apps, data SPM and classification tools, and data loss prevention extensions tuned to its various SaaS platforms such as 365, Azure, and Windows endpoints. This extends the AI security features that were originally part of its Defender for Cloud offerings. It has a limited number of third-party integrations. One-month free trials are available, and the entire suite is available for $12.60 per month per user. Microsoft has stepped up its involvement with AI with its Scout, a collection of autonomous AI agents built on top of OpenClaw. It is designed to work with its applications, using built-in security and privacy controls.
OneTrust AI Governance
OneTrust offers AI Governance, a platform that automates compliance and provides continuous monitoring of the AI landscape, across the software lifecycle starting with any AI usage at the beginning of any build. It can detect policy violations, and which AI agents are running. It offers a series of third-party integrations such as Amazon’s Bedrock and Sagemaker; Azure Foundry, ML Studio, and OpenAI; Databricks Unity Catalog and ML flow; and Google Vertex. Its subscription price is based on the number of admin users and number of AI inventory records, although no specifics were provided.
Orca AI-SPM
Orca Security’s AI-SPM is tightly integrated into the company’s security platform. It continues to expand its features, offering detections of more than 50 AI models, including training data and runtime threats, remediation, and support for Model Context Protocol to connect to other Orca-based telemetry. It continues to expand its nearly 100 integrations across SIEM and SOAR systems and various cloud providers’ services. For example, it works with AWS S3, SQS, SNS, CodeBuild, CloudTrail, and Security Hub. It comes with dozens of best-practice security rules that initially focused on compliance. It also alerts when sensitive data is detected inside models and when secrets are exposed. Orca’s overall security platform shows an AWS Marketplace annual pricing that ranges from $84,000 to $360,000, depending on the number of workloads scanned.
Palo Alto Networks AIRS AI Security
Palo Alto Networks has been busy acquiring point security vendors (Dig, ProtectAI, and an offer on Portkey) and incorporating their code into its two major product lines, Prisma and Cortex. You can purchase AI-SPM functionality in either Palo Alto product line, but they cover different aspects of the AI ecosystem. Cortex offers AI-SPM alongside the data and cloud SPMs integrated into the CNAPP suite. Prisma offers AI-SPM as part of a total AI security package called AIRS AI Security, which includes runtime protection, model scanning, and a more comprehensive platform. We focus on AIRS AI, which supports top-level scans of Amazon, Google Cloud, and Azure AI services to discover AI content and can classify and examine model data and secrets and comes with many built-in AI-related policies. Prisma has a long list of third-party integrations, including significant depth in AWS security services. That link will also take you to detailed instructions on how to set up these integrations. To complicate matters further, Palo Alto also sells a separate Prisma secure browser extension that works with these products to protect your endpoints, and that originated from technology it purchased from Talon Cyber Security in 2023. While pricing was not disclosed, our estimate is that AIRS will cost in the low six figures annually.
Proofpoint People Protection Platform
Proofpoint includes a general AI security product as part of its People Protection Platform that covers a wide range of protective services integrated across its other non-AI security tools. It provides runtime inspection of potential AI misconfigurations, as well as policies that include detection of agent, tools, and MCP connections, and it can generate forensic audits of AI interactions. Proofpoint’s general security platform starts at $96,000 annually on AWS Marketplace. It has several integrations with third-party services across the major cloud platform providers.
SentinelOne Singularity Platform
SentinelOne’s Singularity platform offers several AI protective features, including misconfiguration detection, attack path analysis, automated AI inventory and remediation, and integration with a variety of AI PaaS platforms such as Azure OpenAI, Google’s Vertex AI, and various AWS services. It is bundled within the company’s Cloud Native Security tool. Some of these features originated with Singularity’s purchase of Prompt.Security. Access to all the features requires purchasing the enterprise edition, which is offered with custom pricing, but lower feature tiers are available for $80 per year on this public pricing page. There are also numerous integrations with its Marketplace.
Varonis Atlas AI Security
Varonis Atlas AI Security is a multipurpose security platform that offers a variety of modules, including red team/penetration testing, compliance, and third-party risk management. Its AI-SPM module is combined with an AI inventory scanner and can be used to help development teams classify data used in the AI ecosystem, such as scanning for bad AI behavior, leveraging identities improperly, and examining data flows. Automated remediation processes are built into the tool as well. There are several hundred third-party integrations available for a wide collection of security tools, such as JFrog, Jira, Okta, and Salesforce. Varonis has two pricing components; one based on per user and per protected application and an additional price for resource consumption. Atlas is sold on the AWS Marketplace starting at $108,000 per year and free risk assessments are available to qualified customers.
Wiz/Google AI Application Protection Platform
Google has acquired Wiz but kept its operation independent. It has a multipurpose security platform that comes from a strong posture management (cloud and data) background. Its advanced version has been augmented with a comprehensive AI-related series of policies, detection algorithms, and pipeline, model, and data scanners. These are assembled into a separate AI dashboard page. It can also detect AI pipeline abuses, protect AI runtimes, identify and classify tools and agents, map dependencies graphically and suggest remediation steps. It also contains core AI-SPM features such as discovery, attack path analysis, and supply chains. Pricing for the Wiz Advanced bundle on AWS Marketplace is $38,000 annually.
What about AI-SPM pricing?
Pricing and packaging of AI-SPM tools vary widely. Many vendors offer free trials limited to differing periods (an option that is also available on the AWS Marketplace). We pointed out the open-source alternatives earlier, which is also a good way to see how the products work, but we wouldn’t recommend relying on these tools given their lack of recent updates. The only vendors that have (mostly) transparent pricing are Guardrail Technologies (with both free and monthly plans) and SentinelOne (with various annual plans starting at $80 per endpoint). Most of the vendors didn’t want to provide pricing directly but have published pricing on the AWS Marketplace, which can give you a rough indication that most start in the low six figures for annual contracts. For a typical situation with 1,000 users the total could be in the low six-figure range annually.
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