Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs Oasis Security: 2026 Comparison & Alternative
Oasis Security governs what an agent may reach, through policy and short-lived identities; RedactSure, an Oasis Security alternative built for AI agents, tokenizes the screen before the model reads it. RedactSure is an alternative way to think about agent browsing security, because it protects sensitive data as it is rendered on a screen, before an agent uses it.
Security teams looking for an Oasis Security alternative for AI agents are weighing two control points. Oasis Security sits on the access path, where each agent request becomes a short-lived, least-privilege session. RedactSure sits on the screen, replacing the identifiers a CRM renders with consistent tokens before the model reads the page.
One record runs through the page: a sales lead in a CRM the organization bought, holding a contact name, an email address, a phone number and campaign notes, worked by an agent the way a sales coordinator would. What Is Render-Layer Tokenization? defines the approach, and Does Least Privilege Cover What an AI Agent Sees? explains why a narrow permission still leaves the model holding the whole screen.
Key findings
- As an Oasis Security alternative for agent work, RedactSure replaces the values on the rendered CRM screen with consistent tokens before any model reads it, so the agent works the lead as LEAD_001 and the real value is released only at an approved destination (What Is Render-Layer Tokenization?).
- Scoped access still leaves the model receiving whatever the permitted screen shows; OWASP lists "Personal identifiable information (PII) may be disclosed during interactions with the LLM" as a risk (OWASP, LLM02, 2025).
- A named person approves every payment, submission and record change the agent proposes, a decision no session policy makes (What Is Supervised Delegation?).
- Oasis Security places its control on the access path rather than on the screen: Oasis AAM "sits between your agents" and "the systems they touch (SaaS, cloud, on-prem, data platforms)" (Oasis Security, Introducing, 2025).
- Each request "runs on a short-lived, least-privilege identity," and the platform "links every action to a clear trail: Prompt, Intent, Policy, Session, Action," a record of what was granted, not of what the model received (Oasis Security, AAM, 2026).
- Oasis Security's pages describe no control over the values a permitted system shows the model; the worked example grants a session to "Read leads from Salesforce" and states that "The session is monitored and destroyed after use" (Oasis Security, Introducing, 2025).
How do the two compare side by side?
The table sets Oasis Security's own wording beside what a governed environment does, with the check a buyer can run.
| Dimension | Oasis Security, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "It sits between your agents" and "the systems they touch" (Oasis Security, Introducing, 2025) | On the screen the agent works in, before any model reads it | Where a value is replaced |
| How coverage starts | "Oasis AAM turns agent requests (prompts, tool calls, or action plans) into governed sessions" (Oasis Security, Introducing, 2025) | The agent works inside the governed environment; the CRM is unchanged | Whether the agent reaches the CRM as a request or a screen |
| What the model receives | Access, not values: the aim is "blocking risky actions before they reach your data" (Oasis Security, AAM, 2026) | The screen with tokens such as LEAD_001 and EMAIL_001, consistent for the run | One CRM screen, as the model saw it |
| How real values are restored | The agent reads the real records its session permits; "Read leads from Salesforce" is the worked example (Oasis Security, Introducing, 2025) | Released at an approved destination when a named person approves the action | Who authorizes the release, and where |
| Who approves an action | "Policies, not prompts, drive the final decision" (Oasis Security, Introducing, 2025) | A named person approves every payment, submission and record change | A person's name against the action |
| The audit record | "Capture every session: intent, policy, identity, activity, and expiration" (Oasis Security, AAM, 2026) | Every screen as tokens, every action and every approval, exported to the customer's SIEM | Whether the record shows what the model saw |
The two middle columns differ in the object each product governs: Oasis Security governs the session, so its answer to what the model saw is a session record, while RedactSure governs what the agent reads, and its answer is the screen itself. They also differ on who turns a token back into a real value: a policy on Oasis Security's pages, a named person in RedactSure's design (What Is Supervised Delegation?).
What does Oasis Security protect, and where does it act?
Oasis Security governs non-human identities and agent access. Its product overview says the platform "Auto-discovers all Non-Human Identities," a watch over identities rather than over record values (Oasis Security, Product Overview, 2026). For agents, "AAM understands an agent's intent in real time and applies your policies automatically," aiming at "blocking risky actions before they reach your data" (Oasis Security, AAM, 2026). On ownership, the July 28, 2026 post states "We have signed a letter of intent to be acquired by Cyera" and that "The Oasis Platform continues" (Oasis Security, Next-Generation, 2026); by October 23, 2026 the home page stated that Oasis has been acquired by Cyera, compared in RedactSure vs Cyera: 2026 Comparison & Alternative.
Each benefit depends on one condition: the agent's work reaches a system as a request the platform can see and scope. What the permitted system then renders is outside that condition; the pages describe no change to the values it shows the model once the session is granted, a limit of where the control sits rather than a defect.
Oasis Security's public documentation describes turning agent requests into governed sessions, and does not describe replacing the values an agent reads on a screen with tokens it can work with (How Many AI Security Products Control What an AI Agent Sees?).
What does an agent read when it opens a sales lead record?
The agent's session is scoped to the leads its campaign needs, which is the worked example Oasis Security gives: a request to "Read leads from Salesforce" becomes a governed session, and "The session is monitored and destroyed after use," with nothing on that path changing what the record displays (Oasis Security, Introducing, 2025). The screen shows the contact's name, email address, phone number and campaign notes, and the model receives all four, because the CRM renders a record the same way for anyone. The exposure is in the model, where OWASP places it: disclosure during interactions with the LLM "can result in unauthorized data access, privacy violations, and intellectual property breaches" (OWASP, LLM02, 2025).
An agent that borrows a sales coordinator's browser session also leaves the coordinator's name in the CRM log, so the only separate record of its work is what its environment wrote down (What Is an AI Control Record?). Either way the values were read in full, the point What Is Least Exposure? makes about permission models: they decide reach, and a minimally privileged agent still holds every record it was shown.
Which control fits which work?
Keep Oasis Security for
- Discovering and governing non-human identities, with automated "NHI provisioning, monitoring, and decommissioning" (Oasis Security, Product Overview, 2026).
- Scoping each agent request: "purpose-bound, short-term access for agents; live monitoring for drift and instant block on violations" (Oasis Security, Solution Brief, 2025).
- Bounding delegated permissions: "you can prevent unintentional exposure, such as an AI agent accessing entire storage systems via OAuth" (Oasis Security, AI-SPM, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives LEAD_001 and EMAIL_001 instead of the contact's name and address (What Is Render-Layer Tokenization?).
- A named person approving each payment, submission or record change the agent proposes (What Is Supervised Delegation?).
- The record of what the model received on every screen, exported to the customer's SIEM (What Is an AI Control Record?).
An organization running agents usually needs both, since each covers work the other leaves untouched.
How do you test it on one workflow?
Run the comparison on one real workflow, with both vendors present and every answer written down.
Step 1. Choose a workflow the agent will run, such as updating campaign notes on inbound leads, and pick one screen from it, the lead record.
Step 2. Have each vendor produce the lead screen in the form the model received it. A session trail answers who was granted what; the screen answers whether the model saw the email address or EMAIL_001.
Step 3. List every application in the workflow and mark each as covered or not: for an access control, whether the agent's requests pass through it; for a screen control, whether the application renders inside the governed environment. The uncovered count is the first-day exposure.
Step 4. Trace one value, the phone number, from the screen back to the action that released it to the dialer, when, and whose name is in the record. A session record shows the read was permitted; ask what shows the release.
Step 5. Calculate first-day coverage: if the task list touches five applications and the agent's requests to two pass through the access control, that control covers two of five. Compare the costs that differ: the policy work before each application is governed, and the agent work delayed until it is.
What does a governed environment change?
A governed environment is a class of control. The agent runs under a session of its own and sees a different page from the sales coordinator because the values are replaced with consistent tokens before the model reads anything: the lead appears as LEAD_001, with EMAIL_001 and PHONE_001, throughout the run. Real values resolve only at approved destinations at the moment of an approved action, a named person approves every payment, submission and record change, and every screen, action and approval is written to a control record that exports to the organization's SIEM.
OWASP notes that "Indirect prompt injections occur when an LLM accepts input from external sources, such as websites or files," and its mitigation is to "Restrict the model's access privileges to the minimum necessary for its intended operations" (OWASP, LLM01, 2025). A CRM screen with free-text campaign notes is such a source, and a model that only received LEAD_001 cannot be talked into disclosing a value it never held. The same boundary applies to a control at the tool call, as RedactSure vs Silverfort: 2026 Comparison & Alternative shows.
The approval has a pace problem. Harry Ghuman (CEO, Alpha Decisions) described it on the HAL podcast: the AI can produce "these decisions like thousands of times faster than a person can actually do anything about them" (What Is the AI Delegation Frontier? Harry Ghuman on Who Gave the AI Its Authority).
What the record shows
Who decides what the model receives when an agent opens a contact record, and whose name sits on the release? A render-layer control answers it on the screen: the contact's name, email address and phone number become tokens on the lead record before the model reads it, real values are released only for an approved action, and the record holds the screen the model received. That is what RedactSure, as the Oasis Security alternative for agent work, does for this record. Oasis Security's own post says that "AI adoption runs through the same two control points: access and data," and its pages cover the first: a short-lived session per request, with a trail from prompt to action (Oasis Security, Next-Generation, 2026). The test takes one agent and one lead record: have each vendor show that screen in the form the model received it, then trace the phone number to the action that released it and the person who approved it.
Methodology and limitations
This page draws on seven Oasis Security pages, two OWASP entries and existing RedactSure research pages. Vendor pages were read between October 21, 2026 and October 23, 2026, and each Sources line carries the date for its page. Public documentation read in full gives a sound view of where each product applies its control; where this page says a source does not describe something, it refers to the pages reviewed.
The products on this page are described from documentation; none was tested for this page, both products change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The lead record is an illustrative record type. Compliance determinations belong to counsel, assessors and the organization's security team, and nothing replaces a pilot of one workflow on its own screens.
Frequently asked questions
Does Oasis Security protect the data an agent reads from a permitted system?
Not from the pages reviewed. Oasis Security's pages describe the access an agent is granted: a short-lived identity per request, policies applied to intent, and risky actions blocked before they reach the data. Once a request is permitted, the agent reads the records the session covers, as the worked example of reading leads shows. Protecting the values inside a permitted record is a separate control.
Does Oasis Security change what an agent reads on a CRM screen?
No. The platform sits between the agent and the systems it touches, so its decision comes before the CRM renders anything, and the CRM displays the record the same way for an agent as for a person. The pages describe no masking, tokenization or substitution of values on that screen. A buyer who needs the model to receive LEAD_001 rather than a name needs a control at the screen.
Who approves the agent's action, a policy or a person?
A policy, on Oasis Security's pages, whose "function is to decide what that agent should do, what it does in real time and whether those align" (Oasis Security, Agent 365, 2026). That decision is written in advance and applied to each request. In RedactSure's design a named person approves each payment, submission or record change when the agent proposes it, and the approval carries that person's name.
Does the session record show what the model received?
No. The record Oasis Security describes captures intent, policy, identity, activity and expiration for each session, with a trail from prompt to action. That is a record of what was granted and done; it does not hold the screen as it was shown to the model, so it cannot show whether the model saw a phone number or PHONE_001. RedactSure's AI Control Record holds that screen, as tokens, beside each approval.
Does the Cyera acquisition change this comparison?
Not on the pages reviewed. Oasis Security's July 2026 post describes a signed letter of intent and a joint vision in which identity and data security come together, and its home page now states that Oasis has been acquired. The pages describe no shipped joint product and no change to where the Oasis platform acts. Compare the controls each page documents today and revisit when a combined product is described.
Does an agent need both an access control and a screen control?
Usually, yes. An access control decides which identity may reach which system and for how long, and leaves a trail of each session. A screen control decides which values the model receives from the records that access permits, who approves the resulting action and what record of the screen exists. The first does not cover the second, so an organization running agents in bought applications needs one of each.
How RedactSure closes the screen-level gap in agentic access management
An access control decides which records an agent may open, and the model then reads every value the permitted CRM screen displays. Oasis Security's own worked example grants a session to "Read leads from Salesforce" and destroys it after use, with the lead values read in full in between.
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the lead record under a scoped session, the screen shows the contact's name and email address, and the model receives both. Inside the governed environment: the same screen shows LEAD_001 and EMAIL_001, and the real address reaches the email tool only when the named sales coordinator approves the send.
RedactSure is deploying now with enterprise and government customers.
Everyone else controls where data can go. RedactSure controls what the AI can see.
See it on your own workflow
Protecting the sensitive data an agent could read on a screen is a needed part of any solution that includes Oasis Security. Bring one CRM workflow and see, with test values, what the model receives and who approves the update. Book a demo