PromptArmor
PromptArmor · AI Detection · Other
PromptArmor is an AI risk intelligence platform that assesses third-party AI vendors, scores their risk across 26 vectors, and monitors permission, model, and data-access changes over time.
About PromptArmor
What Is PromptArmor
PromptArmor is a web platform for security, privacy, and legal teams that have to approve AI tools they don't build. It reads what a vendor publishes about an AI product, turns that into a structured risk assessment, and keeps watching the product after approval. The work it replaces is the spreadsheet-and-questionnaire loop most teams still run by hand.
The focus is the agent supply chain, where AI supply chain security work now concentrates: applications, agents, models, skills, connectors, and plugins that a vendor operates on your behalf. Each of those pieces can read your data, call tools, and pass content to another model. PromptArmor looks at how they combine, then reports where data can leave your environment and where hidden instructions in outside content can steer an agent.
The limits are worth knowing before you sign up. Coverage depends on what vendors disclose, so an assessment reflects public documentation and research rather than hands-on testing of the vendor's systems. The free tier stops at five applications and one month of monitoring, and enterprise terms are quoted by sales rather than listed.
Getting Started
- Book a demo or start the free trial, then add the AI vendors you already use. You can add up to five applications at no cost.
- Pick an asset to review. PromptArmor covers applications, agents, models, skills, connectors, and plugins, and you choose which one you need to clear first.
- Read the risk report. Every asset comes with a score across 26 risk vectors and a mapping to NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS so the findings fit a framework your team already reports against.
- Check the exposure sections. The prompt injection and data privacy views show connector scope, training defaults, retention terms, and AI subprocessors.
- Connect the output to your existing workflow. Reports can be pushed into tools such as ServiceNow, ProcessUnity, Zscaler, Netskope, or Archer, and enterprise accounts can pull the same data through the API.
Product Information
A quick look at PromptArmor's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Third-party risk analysts
- CISOs and security leads
- Privacy and legal teams
- Procurement and vendor management
Tasks
- Assessing a new AI tool before rollout
- Reviewing indirect prompt injection exposure
- Tracking vendor changes after approval
- Documenting AI subprocessors for privacy reviews
- Reporting AI risk to a board or auditor
Scenarios
- A quarterly vendor review where a dozen AI tools sit in the portfolio and each one has shipped updates since the last check.
- Shadow AI discovery, when employees sign up for tools that never went through procurement and someone has to catch up fast.
- A regulated industry review, where the risk file needs citations to NIST AI RMF or OWASP LLM Top 10 before an auditor accepts it.
- Pre-renewal due diligence, when a vendor adds an agent feature and the contract is the only place left to raise data handling.
Key features
AI Asset Inventory
PromptArmor catalogues the AI pieces a vendor actually runs: applications, agents, models, skills, connectors, and plugins. That breakdown matters because a chatbot and an agent with a connector to your document store carry very different exposure. The inventory is the base every other view builds on, so a gap here weakens the rest of the report.
Risk Scoring Across 26 Vectors
Each asset gets a score built from 26 risk vectors rather than a single pass or fail label. Scores map to NIST AI RMF, OWASP LLM Top 10, and MITRE ATLAS, which means findings can drop into a report your compliance team already uses. The result reads as a comparative view across vendors, not an absolute safety verdict.
Indirect Prompt Injection Analysis
This is the capability the company is best known for. The platform looks at how an AI application is built, what its connectors can reach, and what data access it holds, then shows where hidden instructions in outside content could redirect the agent. Reports describe the route an attacker would take, so a security team can decide whether a control or a contract clause closes it.
Continuous Change Monitoring
Vendors ship new models and wider permissions between reviews. PromptArmor watches the portfolio and flags changes in AI scope, permission, and data access, with a month of continuous monitoring included in the free trial. The practical effect is that a review becomes a standing process instead of an annual scramble.
Data Privacy and Subprocessor Mapping
The privacy view answers a narrow set of questions that come up in every AI contract: does this vendor train on your data by default, which AI subprocessors touch it, and how long is it retained. It also covers training opt-out policies and retention obligations. Teams use it to spot vendors that never cleared procurement, which is where most shadow AI sits.
Workflow Integrations and Enterprise Controls
Reports move into ServiceNow, ProcessUnity, Zscaler, Netskope, and Archer, so AI risk lands where vendor risk and enforcement already live. Enterprise plans add API access, native connectors, role-based access control, and SSO with OAuth identity management. Smaller teams can work inside the PromptArmor interface and skip the integration work until the portfolio grows.
Pros and cons
Pros
- The 26 risk vectors and framework mappings give a review a structure that survives an audit question.
- Indirect prompt injection analysis is specific about connector scope and data access, which generic vendor questionnaires rarely cover.
- Continuous monitoring catches permission and model changes, the category of update that normally slips past an annual review.
- A real free tier covers five applications with a month of monitoring, enough to test the reports against vendors you already know.
- Integrations with ServiceNow, ProcessUnity, Zscaler, Netskope, and Archer mean the findings don't need a second home.
Cons
- Assessments rest on vendor disclosures and PromptArmor's research, so a vendor that publishes little produces a thin report and someone has to follow up.
- Enterprise pricing is quoted by sales, which slows budgeting and makes comparison against other AI governance tools harder.
- The free tier stops at five applications, so a mid-size portfolio hits the paywall during evaluation.
- There's no on-premises option listed, which rules it out for teams that can't send vendor data to a SaaS platform.
Frequently asked questions
PromptArmor assesses and monitors the AI products your vendors run. It builds an inventory of their AI assets, scores risk across 26 vectors, analyses indirect prompt injection exposure, and tracks changes in permissions, models, and data access.
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