No solution approach in the current research connects this vendor to this use case.
Vendor research
Oasis Security
Review what this vendor says publicly, the security topics those statements may support, what remains unverified, and factual company context. This is not an assessment of product effectiveness or fit.
Use-case context
How this vendor relates to the selected use case
No related approach foundBack to use case →
These links show approaches associated with this vendor. The relationship label describes how the approach maps to the use case—not product effectiveness, complete requirement coverage, or fit.
Company scale
Scaled?
ScaledA private provider with at least $100M in known funding or at least 250 employees.This is a company-scale signal, not a product-quality rating.
?
ScaledA private provider with at least $100M in known funding or at least 250 employees.This is a company-scale signal, not a product-quality rating.A descriptive band derived from retained public revenue, workforce, ownership, or funding signals.
Company scale is separate from product features, effectiveness, and suitability.
- $195M known funding
- 50-250 employees
Company context
Private, VC-backed
Reported total funding around $195M after the 2026 Series B
Research coverageCounts describe available public research, not product quality.View details
- Vendor statements
- 19 records
- Source-checked records
- 12
- Evaluation requirements
- 19 in this research model
- Unresolved requirements
- 7
Company intelligence
Who is behind the product
Company facts provide evaluation context. Each signal is kept separate because tenure, workforce, funding, and hiring answer different questions.
Founded2022
HeadquartersNew York, New York; Israeli R&D roots
OwnershipPrivate, VC-backed
Employees50-250
Capital and scaleIndependent company
Oasis Security
- Known funding
- $195M
- Operating scale
- Reported total funding around $195M after the 2026 Series B
- Backing context
- $120M Series B led by Craft Ventures; existing investors include Cyberstarts, Sequoia Capital, and Accel
Series B · $120M · 2026-04-07
Named investors
Sequoia Capital · Accel · Craft Ventures · Cyberstarts
Founders and leadership2 people listed
- Danny BrickmanCurrent role listed
Co-Founder & CEO
- Amit ZimermanCurrent role listed
Co-Founder & CPO
Operating signalsRead each signal separately
There is no combined company rating. The company-scale label uses stated size thresholds; product features and effectiveness require separate evidence.
- Company tenure
- 2022
- Workforce scale
- 50-250
- Hiring activity
- 70 open positions · growing
A hiring count is shown only when a clickable source is available.
Greenhouse careers board ↗Core company facts have supporting public sources.
Company sources and research limits6 linked public sources
Only company facts supported by retained public sources are shown. Missing values remain unknown, and company scale does not establish product effectiveness.
Company sourceOasis homepageOasis lists its New York headquarters address in the site footer.Company sourceFinSMEs Series B profileOasis raised $120M Series B and was founded in 2022 by Danny Brickman and Amit Zimerman.Company information sourceStored company websiteSupports the company facts shown in this profile.Company information sourceGreenhouse careers boardSupports the company facts shown in this profile.Company information sourceOasis Security company and leadership pageSupports the company facts shown in this profile.Company information sourceOasis Security funding and leadership announcementSupports the company facts shown in this profile.
Solution areas
These areas describe how the vendor approaches enterprise AI security. They do not establish product quality or fit.
Buyer context
- One of the more heavily funded non-human identity (NHI)/agentic-access vendors in this set, with stronger enterprise buying-signal credibility.
- Commercial diligence should focus on how agentic access management overlaps with existing identity and access management (IAM), PAM, vault, and IGA tooling.
Related frameworks
Where public vendor statements relate to framework requirements
11 related frameworks · expand when needed
Related frameworks
Where public vendor statements relate to framework requirements
These links show related requirements for further review. They do not establish framework compliance or control implementation. Open the full framework crosswalk →
Current referenceCIS Critical Security Controls
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 58
- Requirements with public support
- 11
- Related requirements
- 14
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 35
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 71
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 39
- Requirements with public support
- 11
- Related requirements
- 12
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 11
- References
- 27
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 31
- Requirements with public support
- 11
- Related requirements
- 13
- References
- 25
- Requirements with public support
- 3
- Related requirements
- 3
- References
- 3
Evaluation questions
What to verify beyond public claims
These questions come from security requirements with some public support. Use them as starting points for demonstrations, documentation review, customer references, or a buyer-observed pilot.
- 01Unapproved AI use discovery
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
- 02Unapproved AI use discovery
The test user's AI usage activity can be filtered or exported with AI-specific context.
- 03Approved AI usage monitoring
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
- 04Approved AI usage monitoring
Prompt, model, or admin activity can be exported or correlated for the selected approved AI platform.
- 05Controls for unapproved AI use
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
- 06Controls for unapproved AI use
The control event records policy reason, user, destination, action, and timestamp.
- 07AI governance, risk, and compliance
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
- 08AI governance, risk, and compliance
A policy, assessment, approval, exception, or remediation workflow changes the governed state of the test system.
Detailed security-requirement research18 evaluation items · supporting evidence and open research are shown separatelyExpand
Security requirementPublic supportRelated frameworksWhat to verify
Unapproved AI use discovery
Limited public supportDiscover and monitor workforce AI tools, accounts, prompts, domains, models, users, and usage outside approved controls.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An unmanaged AI app used by a test user appears in discovery inventory with user, app or domain, and timestamp.
AI-feature discovery in business applications
No supporting claim foundInventory software as a service (SaaS) applications that embed AI features, expose enterprise data to AI capabilities, or create AI-driven data movement.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A software as a service (SaaS) app with an embedded AI feature appears in the software as a service (SaaS) AI inventory with app, provider, and feature context.
Approved AI usage monitoring
Limited public supportMonitor approved AI workspaces, tenants, gateways, and model platforms such as ChatGPT Enterprise, Claude Enterprise, Gemini, Microsoft Copilot, Vertex AI, Elvex, or internal AI gateways.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Approved AI workspace activity appears with user, workspace or tenant, model or provider, and timestamp.
Controls for unapproved AI use
Limited public supportBlock, coach, redirect, or contain non-approved AI use and policy-violating AI interactions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A policy blocks, coaches, redirects, or contains a test interaction with an unapproved AI destination.
Sensitive-data protection for generative AI
No supporting claim foundDetect, classify, redact, or block sensitive data in prompts, responses, files, retrieval, memory, and AI-connected workflows.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
Sensitive prompt, response, or file test data is detected and classified during an AI interaction.
Browser and business-application controls
No supporting claim foundApply session-level controls in browser and software as a service (SaaS) workflows, including uploads, downloads, copy/paste, sharing, and identity-aware access decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A session-level policy controls upload, download, copy, paste, sharing, or form submission in a browser or software as a service (SaaS) workflow.
Generative AI application security
No supporting claim foundProtect enterprise-built large language model (LLM) applications, retrieval-augmented generation (RAG) systems, prompts, application programming interfaces (APIs), model calls, tools, and production runtime behavior.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test large language model (LLM) application event records prompt, application programming interface (API), model, retrieval, or tool interaction context.
AI governance, risk, and compliance
Strong public supportInventory AI systems and owners, translate policy and regulatory obligations into governed workflows, assess risk, manage approvals and exceptions, and retain audit evidence across the AI lifecycle.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test AI system is registered with owner, intended use, risk tier, lifecycle state, and applicable obligations.
AI assurance and adversarial testing
No supporting claim foundTest models, applications, retrieval-augmented generation (RAG) systems, and agents before release and continuously thereafter using adversarial probes, evaluation suites, attack simulation, and security release gates.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A controlled test campaign exercises an AI model, application, or agent against named AI attack classes.
AI model and supply-chain security
Limited public supportDiscover, inventory, scan, validate, and monitor models, datasets, model artifacts, registries, dependencies, and AI development assets for tampering, unsafe serialization, provenance gaps, or malicious content.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test model or AI artifact appears in inventory with origin, version, hash or provenance, and deployment context.
AI gateway, tool-connection, and runtime controls
Strong public supportMediate model, agent, tool, application programming interface (API), connector, and Model Context Protocol (MCP) traffic through an enforcement point that applies identity-aware policy, content controls, routing, rate limits, and auditable allow or deny decisions.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A model, agent, tool, or Model Context Protocol (MCP) request passes through a named policy enforcement point.
Action-taking agent monitoring
Strong public supportObserve and govern agent plans, memory, tool calls, delegated tasks, autonomy, runtime decisions, and outcomes.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent run captures plan, steps, tool calls, outcome, and timestamps.
Agent-to-agent communication security
Limited public supportAuthorize, log, and control agent-to-agent, agent-to-tool, Model Context Protocol (MCP), connector, and tool-chain handoffs.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
An agent, tool, connector, or Model Context Protocol (MCP) handoff logs source identity, destination, and authorization decision.
Non-human identity and service-account security
Strong public supportInventory, least privilege, credential hygiene, monitoring, and lifecycle management for non-human identities, workloads, service accounts, application programming interface (API) keys, and machine credentials.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test service account, agent identity, or non-human identity appears in inventory with owner and privileges.
AI agent identity and permissions
Strong public supportRegister AI agents as accountable identities, bind them to owners and delegating users, authorize task- and tool-level access, issue short-lived credentials, review access, and revoke or suspend agent authority.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test agent is registered with a unique identity, accountable owner, purpose, and permitted resources.
AI coding-agent and workstation security
Strong public supportDiscover and govern AI coding agents, integrated development environment (IDE) assistants, command-line agents, skills, hooks, extensions, Model Context Protocol (MCP) tools, filesystem access, commands, network activity, secrets, and software-supply-chain actions on developer workstations and build environments.
NIST AI RMF PlaybookNIST Cybersecurity Framework 2.0CIS Critical Security ControlsISO/IEC 42001OWASP GenAI Security Solutions Landscape
A test coding agent and its skills, hooks, extensions, or Model Context Protocol (MCP) tools appear in an attributable inventory.
AI cost and usage controls
No supporting claim foundVisibility, attribution, budgeting, rate limiting, anomaly detection, and optimization for AI usage and spend across models, agents, workflows, and owners.
Commercial MetadataNIST AI RMF PlaybookNIST Cybersecurity Framework 2.0ISO/IEC 42001OWASP Agentic AI Security Solutions Landscape
A controlled AI usage event is attributed to user, team, model, workflow, or owner with cost or token metrics.
Licensing model
No supporting claim foundPublicly discoverable commercial model such as per user, per seat, per app, per token, per integration, or enterprise platform license.
The vendor can map the sourced commercial model to per-user, per-seat, per-app, per-token, per-integration, or platform packaging.
Public sources
Vendor statements and quoted evidence
Showing the first 6 of 19 source records. Open additional records only when needed.
Oasis claims agent discovery, inventory, ownership, credential governance, policy-driven approvals, chain-of-custody evidence, regulator-ready auditability, and lifecycle control for AI agents and non-human identities.
Every session generates a complete chain of custody: Human → Agent → Prompt → Intent → Policy → Identity → Actions → Results.
Oasis Agentic Access Management materials reviewed did not provide a public product claim for automated adversarial testing, repeatable attack suites, model or agent red teaming, or release-gate evaluation.
No quoted source text is recorded for this claim.
Oasis claims security-posture and credential-exposure evaluation for AI providers, Model Context Protocol (MCP) servers, third-party agents, scripts, and tools before access, including allowlisting and onboarding of vetted Model Context Protocol (MCP) components.
Organizations evaluate AI providers, MCP servers, and third-party agents for security posture, data handling, and credential exposure before granting access.
Oasis claims intent-aware runtime policy that converts prompts, tool calls, and action plans into short-lived least-privilege sessions with allow, warn, deny, or step-up enforcement before execution.
Every interaction is turned into a short-lived, least-privilege session with full accountability.
Oasis claims agent lifecycle governance, accountable ownership, just-in-time ephemeral identities, deterministic intent-aware authorization, precise scopes, session expiry, continuous oversight, and end-to-end attribution.
Granted via just-in-time, ephemeral identities.
Oasis claims Cursor hook and policy integration that attributes coding-agent actions, vets Model Context Protocol (MCP) servers, blocks high-risk shell and Git operations, applies data loss prevention (DLP) to tool payloads, and requires step-up approval for production actions.
Command guardrails: detect high-risk shell commands and deny or step-up based on policy.
Show 13 additional evidence records
Oasis Security agentic access materials reviewed did not provide a public product claim for AI usage-cost attribution, token or spend metrics, budgets, chargeback, or cost-aware model routing.
No quoted source text is recorded for this claim.
Oasis Security claims complete visibility and control across all AI platforms.
Know exactly what's happening across all your AI platforms, with complete visibility and control.
No public claim found for this capability.
No quoted source text is recorded for this claim.
Oasis Security claims visibility and control across AI platforms, including agent, identity, and permission mapping.
Know exactly what's happening across all your AI platforms, with complete visibility and control.
Oasis Security claims policy guardrails can approve or block agent actions and enforce least-privilege access at runtime.
blocking risky actions before they reach your data.
No public claim found for this capability.
No quoted source text is recorded for this claim.
Oasis Security claims its agentic access platform captures every session and shows each ephemeral identity, granted access, and real-time activity.
Capture every session: intent, policy, identity, activity, and expiration, for total visibility and compliance.
Oasis Security claims policy-controlled agentic access management for agent actions, sessions, and cross-system resource access.
Prompt, Intent, Policy, Session, Action
Oasis Security claims it secures AI agents and non-human identities across IaaS, software as a service (SaaS), PaaS, and on-prem environments.
Oasis secures AI agents and non-human identities across IaaS, SaaS, PaaS, and on-prem environments
No public claim found for this capability.
No quoted source text is recorded for this claim.
No public claim found for this capability.
No quoted source text is recorded for this claim.
No public claim found for this capability.
No quoted source text is recorded for this claim.
Oasis Security claims it secures AI agents and non-human identities across IaaS, software as a service (SaaS), PaaS, and on-prem environments including ChatGPT, Salesforce, Office 365, and Copilot.
Oasis secures AI agents and non-human identities across IaaS, SaaS, PaaS, and on-prem environments, from AWS, Azure, and BigQuery to GitHub, ChatGPT, Salesforce, Office 365, and Copilot.