What Prompt Security Built - And Its Limits
Prompt Security positioned itself as a GenAI security platform focused on protecting organisations from prompt-level threats. Its browser-based approach intercepted AI interactions at the browser layer, providing visibility into which AI tools employees accessed and scanning prompts for sensitive data and adversarial inputs.
The browser-based approach had a genuine advantage: it could monitor any web-based AI tool without requiring API-level integration. If an employee used ChatGPT, Claude, Gemini, or any other browser-based AI tool, Prompt Security could see and scan the interaction.
But Prompt Security's scope remained firmly within prompt security - its category and its name. It answered "Is this prompt safe?" while leaving the broader governance questions unanswered:
- Who should be allowed to use which models, for which purposes? (Limited policy engine)
- Should sensitive data be masked rather than blocked? (No masking capability)
- Is the AI advising or deciding? Where are the boundaries? (No decision authority controls)
- Can we explain to a regulator why a specific decision was made? (No decision provenance)
- What exactly did the AI see during an incident? (No incident replay)
- What is our total model exposure across the organisation? (No model registry)
- Can we produce audit-ready evidence, not just security logs? (No compliance mapping)
These gaps are not criticisms of what Prompt Security built - they are the natural limitations of a tool designed for prompt security rather than AI governance.
The SentinelOne Acquisition: What Changed
In September 2025, SentinelOne acquired Prompt Security for an estimated $250–300M. At the time, Prompt Security had approximately 30 employees and minimal disclosed revenue - making this a strategic acquisition priced on technology and talent rather than revenue metrics.
The acquisition fits SentinelOne's pattern of expanding its Singularity platform into adjacent security categories. Prompt Security's browser-based AI monitoring complements SentinelOne's endpoint detection and response (EDR) capabilities - AI security becomes another data source in the Singularity telemetry pipeline.
For customers, the implications are familiar - the same pattern that played out with Lakera (→ Check Point), Protect AI (→ Palo Alto), and five other AI security acquisitions in 2024–2025:
- Standalone product sunset. Prompt Security is no longer available as an independent product. New customers access it as a module within SentinelOne Singularity.
- Ecosystem dependency. Using the AI security module now requires a SentinelOne subscription - endpoint agents, cloud workload protection, or identity security at minimum.
- Roadmap dilution. Prompt Security's team now serves SentinelOne's broader platform roadmap. AI governance improvements compete with EDR, cloud security, and identity protection for engineering priority.
- Pricing rebundling. What was a focused, affordable SaaS product becomes a module within an enterprise platform with enterprise minimum commitments.
If you are evaluating Prompt Security today, you are evaluating SentinelOne Singularity with an AI security add-on - a fundamentally different purchasing decision than the original standalone product. For an independent, purpose-built alternative, see how Areebi compares.
Browser-Layer Security vs Application-Layer Governance
Prompt Security's browser-based approach provided a specific advantage: it could monitor AI interactions without requiring API integration or infrastructure changes. A browser extension observed what employees typed into any web-based AI tool and flagged or blocked sensitive content.
This is clever engineering - but it operates at the wrong layer for comprehensive governance.
What browser-layer security can do
- Detect when employees access web-based AI tools
- Scan prompt text before it is submitted
- Block or alert on sensitive data patterns in prompts
- Provide visibility into shadow AI usage (browser-based only)
What browser-layer security cannot do
- Govern API-based AI usage (developer integrations, automated pipelines, embedded AI features)
- Scan model responses for data leakage or policy violations
- Enforce identity-aware, role-based, context-dependent policies
- Provide a governed AI workspace that replaces shadow AI tools
- Generate compliance-mapped audit evidence
- Replay incidents with full model context
- Mask or tokenize data while preserving prompt utility
- Track model inventory and risk exposure across the organisation
Areebi operates at the application layer - governing the full AI interaction lifecycle from workspace to model to response. This includes browser-level capabilities (shadow AI detection via browser extension) but extends to API governance, policy enforcement, compliance automation, and every other governance layer that browser-only tools structurally cannot reach.
| Layer | Browser security (Prompt Security) | Application governance (Areebi) |
|---|---|---|
| Web-based AI tools | Yes - browser extension | Yes - workspace + browser extension |
| API-based AI usage | No | Yes - API gateway governance |
| Embedded AI features | No | Yes - policy enforcement layer |
| Model responses | Limited | Yes - output enforcement |
| Policy enforcement | Basic allow/block | Granular: allow / mask / block / approve |
| Compliance evidence | No | Yes - framework-mapped packages |
The browser layer is a detection point. The application layer is a governance platform. Organisations need both - which is why Areebi includes browser-level detection as one component within a comprehensive control plane.
The Governance Capabilities Prompt Security Never Built
Of the 14 governance capabilities in the CTO's evaluation matrix, Prompt Security covered 5 (most partially). Areebi covers all 14. The critical gaps:
No data masking
Prompt Security could detect sensitive data and block the prompt - but it could not mask or tokenize data to preserve prompt utility. This forced a binary choice: allow the prompt (with sensitive data) or block it entirely. Areebi's native masking offers a middle path - remove the sensitive data while preserving the prompt's analytical value.
No policy engine
Prompt Security had basic access rules but no identity-aware, context-aware policy engine. It could not enforce rules like "The finance team can use AI for analysis but not for customer-facing communications" or "Contractors can access Llama but not GPT-4." Areebi's policy builder supports these granular, conditional policies with a visual interface.
No decision authority controls
As AI shifts from advisory to autonomous, organisations must enforce boundaries between "AI recommends, human decides" and "AI decides independently." Prompt Security had no mechanism for this classification or enforcement - a growing source of regulatory liability under the EU AI Act.
No decision provenance
When a regulator asks "Why was this AI interaction handled this way?", Prompt Security could not provide a provenance trail. Areebi captures the complete decision chain: which policy was evaluated, what data was assessed, which rule triggered, what action was taken, and the full context of the evaluation.
No incident replay
Unique to Areebi: when an AI incident occurs, the platform can reconstruct exactly what the model saw - the full prompt context, policy state, model version, and user permissions at the time of failure. This is essential for forensic investigation, regulatory response, and post-incident learning.
No audit-ready evidence
Prompt Security generated security logs. Areebi generates compliance evidence - pre-mapped to HIPAA, SOC 2, ISO 27001, NIST AI RMF, and the EU AI Act. The difference: logs tell you what happened; evidence proves you were governing correctly.
Pricing: From Focused SaaS to Enterprise Bundle
Prompt Security's original pricing was accessible - a SaaS product priced per user for browser-based AI monitoring. Post-acquisition, the economics change fundamentally.
SentinelOne Singularity with AI Security (formerly Prompt Security)
| Component | Estimated annual cost |
|---|---|
| SentinelOne Singularity platform (prerequisite) | $50,000–$120,000 |
| AI Security module | $15,000–$35,000 |
| Implementation services | $15,000–$30,000 |
| Total (200 users) | $80,000–$185,000 |
Areebi (complete AI control plane)
| Component | Annual cost |
|---|---|
| Areebi platform (200 seats, all capabilities) | $48,000–$84,000 |
| Implementation | $5,000 (one-time) |
| Total Year 1 | $53,000–$89,000 |
Areebi delivers 34–52% cost savings compared to SentinelOne's AI Security module - while providing 14 governance capabilities vs 5 and requiring no prerequisite platform. See transparent pricing on our website.
Beyond direct cost, Areebi eliminates the vendor lock-in that platform bundles create. SentinelOne's AI Security module only operates within the Singularity ecosystem - switching endpoint protection means losing your AI governance. Areebi deploys independently in your VPC, on-prem, or air-gapped environment, decoupling AI governance from infrastructure vendor decisions.
Migrating from Prompt Security (or SentinelOne AI Security)
Whether you are an existing Prompt Security customer facing SentinelOne migration, or evaluating alternatives before committing to the Singularity platform, Areebi provides a clear transition path.
What carries over
Prompt Security's core capabilities - sensitive data detection, prompt scanning, basic shadow AI visibility - all have direct equivalents in Areebi's platform. Your existing detection rules and sensitivity classifications translate to Areebi's DLP engine configuration.
What you gain
Every governance capability Prompt Security lacked: native data masking, granular policy engine, decision authority controls, decision provenance, incident replay, model registry, comprehensive shadow AI discovery (browser + network + API), and audit-ready compliance evidence.
You also gain a governed AI workspace - a multi-model environment with RAG, conversation management, and collaboration features. This is the mechanism that makes governance work in practice: employees choose the governed workspace because it is genuinely better than consumer alternatives, not because security forced them.
Timeline
| Phase | Duration | Activities |
|---|---|---|
| Assessment | 1 week | Map existing rules, identify governance gaps, plan capability activation |
| Parallel deployment | 1–2 weeks | Run Areebi alongside existing setup, validate detection parity |
| Cutover | 1 week | Activate enforcement + additional governance capabilities |
| Expansion | Ongoing | Enable policy engine, compliance templates, workspace rollout |
Total migration: 3–4 weeks. Request a demo to see the migration path specific to your setup, or take the free AI governance assessment to understand your current governance gaps.
Frequently Asked Questions
Is Prompt Security still available as a standalone product?
No. Prompt Security was acquired by SentinelOne in September 2025 for $250–300M. The standalone product has been integrated into SentinelOne's Singularity platform. New customers must purchase SentinelOne Singularity to access the AI Security module. Existing Prompt Security customers face migration timelines set by SentinelOne.
Prompt Security had good browser-based shadow AI detection. Does Areebi match this?
Areebi matches and exceeds Prompt Security's shadow AI detection. Areebi's browser extension detects AI tool usage across 50+ platforms - comparable to Prompt Security's browser-based approach. But Areebi adds network-level detection for API-based AI usage and embedded AI features that browser-only tools cannot see. The combination provides comprehensive shadow AI visibility across all access methods, not just browser-based tools.
We liked that Prompt Security was lightweight and non-intrusive. Is Areebi heavier?
Areebi is designed for progressive activation. You can start with lightweight capabilities - shadow AI detection via browser extension, DLP scanning, basic policies - and enable deeper governance features as your programme matures. The workspace, compliance automation, and incident replay capabilities are available when you need them but do not impose overhead until activated. Many customers deploy Areebi in monitoring mode first, then activate enforcement after validating detection accuracy.
How does Areebi handle the use case of monitoring employees using consumer AI tools?
Two complementary approaches. First, Areebi's browser extension provides visibility into which consumer AI tools employees access, what they type, and what data leaves the organisation - similar to what Prompt Security offered. Second, and more importantly, Areebi provides a governed AI workspace that is genuinely better than consumer alternatives. The most effective shadow AI strategy is not just monitoring - it is providing a superior governed alternative that employees voluntarily adopt.
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