Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs E2B: 2026 Comparison & Alternative
E2B keeps a credential outside the sandbox and injects it at the egress proxy, while RedactSure, an E2B alternative built for AI agents, replaces screen values before any model reads them. 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.
What does the model receive when a coding agent runs in E2B, and which E2B alternative changes that answer at the screen? RedactSure, an E2B alternative built for AI agents, replaces the values a page shows with consistent tokens before the model reads them. E2B applies its control to the sandbox and its outbound request: a credential is stored with E2B, referenced by name, and injected by the egress proxy on a matching request, which bounds the credential, not the page. RedactSure applies its control where the page is drawn: the key and the customer record reach the model as KEY_001 and ACCT_001, and a real value resolves only where an approved action sends it.
E2B's documentation is quoted here, with one record type: a settings page in a billing console the organization bought, holding an API key and a customer record. What Is a CodeCell? describes the environment that runs the harness, and What Is Least Exposure? sets out the principle.
Key findings
- As an E2B alternative for agent work, RedactSure replaces the values on a rendered screen before any model reads it, so the agent works the account as ACCT_001 and the real value is released only at an approved destination (What Is Render-Layer Tokenization?).
- An agent run cannot supply the two things an auditor asks for, a named approver and a record. FINRA's 2026 oversight report warns that "Agents may act beyond the user's actual or intended scope and authority" (FINRA, 2025).
- The E2B Secrets page describes where a stored value is kept and when it is injected, and it does not state what a model receives from a screen the agent opens inside the sandbox (E2B, 2026).
- E2B lets a team "store credentials such as API keys with E2B and reference them by name," so the sandbox configuration carries a reference rather than the value, which covers the credential and not the screen an agent reads (E2B, 2026).
- The same page states that "The egress proxy injects the real value into matching outbound HTTPS requests outside the sandbox," which keeps a header-borne key out of the process while the rest of the request leaves as written (E2B, 2026).
- E2B draws the line against environment variables, where "any code running in the sandbox can read it," a distinction about the credential that says nothing about the customer record on a page (E2B, 2026).
How do the two compare side by side?
The table sets E2B's own wording beside what a governed environment does on the same point, with the check a buyer can run.
| Dimension | E2B, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "Your sandbox configuration contains only a reference to the secret" (E2B, 2026) | On the screen, before any model reads it | Whether the value ever enters the model's context |
| How coverage starts | "Secrets let you store credentials such as API keys with E2B and reference them by name" (E2B, 2026) | The agent opens the application inside the governed environment, with nothing installed in it | How many of the agent's screens are covered on the first day |
| What the model receives | An environment variable is one "any code running in the sandbox can read it" (E2B, 2026) | The screen with consistent tokens, KEY_001 and ACCT_001, for the whole run | One screen, shown field by field as the model read it |
| How real values are restored | "The egress proxy injects the real value into matching outbound HTTPS requests outside the sandbox" (E2B, 2026) | Released at an approved destination when a named person approves the action | Where the value can go, and who authorized it |
| Who approves an action | The page describes no approval step; the injection follows a request match (E2B, 2026) | A named person approves every payment, submission and record change | A person's name, not a rule |
| The audit record | The page describes no log of what a request carried, and ends at the injection (E2B, 2026) | Every screen as tokens, every action and approval, in the AI Control Record sent to the customer's SIEM | Whether the record shows what the model saw |
The two middle columns describe different objects. E2B governs the sandbox and the request that leaves it, so its answer to what a model read is complete for the credential path it maps and silent about the page. RedactSure governs what an agent reads, and its answer is one record of the screen as tokens. They also differ on who turns a token back into a real value: a request that matches, or a named person (What Is Supervised Delegation?).
What does E2B protect, and where does it act?
E2B runs code in a sandbox, and its Secrets page describes the credential boundary around that code. A team can "store credentials such as API keys with E2B and reference them by name," the configuration "contains only a reference to the secret," and "The egress proxy injects the real value into matching outbound HTTPS requests outside the sandbox" (E2B, 2026), a boundary around the credential rather than the page. Docker's sandbox pages document the same boundary: a host proxy routes egress, since "All outbound TCP traffic from the sandbox routes through a proxy on your host" (Docker, Architecture, 2026), a network boundary, not a content one. Of the four sandbox products reviewed in October 2026, two describe stripping credential values from transcripts and logs, and E2B is one of the two (Can AI Coding Agents Read Your API Keys?).
Each benefit depends on one condition: the value has to be stored with E2B and used by a request whose destination matches the mapping. A key that arrives some other way, in an environment variable the sandbox sets or on a page the agent opens, is outside that path; a variable is one any code in the sandbox can read. gVisor's production guide adds that sandboxing "has a performance penalty" and that a sandbox "should generally not be used to sandbox every application" (gVisor, Production, 2026).
The limit is where the value sits. E2B's page keeps a value outside the sandbox and puts it into a request at the proxy, while the page an agent reads is rendered inside it. gVisor's security model states the point for the class: "A sandbox is not a substitute for a secure architecture" (gVisor, Security, 2026).
What does an agent read when it opens a settings page?
The record is a settings page in a billing console the organization bought, with an API key field and a customer record. E2B's boundary runs around the process and its outbound request, so the application renders the page from its own database and the model receives the key as displayed, along with the customer's name, account number and plan. A stored value being outside the sandbox does not change that: the key on the screen was placed there by the application, not the proxy, and the page reaches the model before any request leaves.
Rishov Chatterjee, AI engineer at Curology and former Director of Data Science and AI at Integra Connect, told a HAL podcast that "data is becoming more and more multimodal as we start to see progression with agent development" (HAL Transcript: Rishov Chatterjee).
The credential half of the design has a documented limit of its own. Docker's isolation page states that "Credential values are never stored inside the VM" (Docker, Isolation, 2026), a statement about the VM; the customer record on the settings page is not a credential, and the page does not describe changing it before the model reads it.
The exposure is in the reading. If the agent works under the account owner's session, the console logs the owner for work the agent did. The arrangement is the one What Is a Tethered Agent? sets out: the agent goes where the person could go, and the session stays the person's.
A key read once stays in the context for the rest of the run, and a customer record read once can be repeated in a summary or a support reply. The page-side alternative is the design What Is a Protected Browser for AI Agents? defines, where credentials and personal data are replaced with placeholders before the agent's view of a page is built.
Which control fits which work?
Keep E2B for
- Workloads that need the credential out of the process, where E2B holds the stored value and the configuration "contains only a reference to the secret" (E2B, 2026).
- Calls to a known host, where "The egress proxy injects the real value into matching outbound HTTPS requests outside the sandbox" (E2B, 2026).
- Runs whose destinations are fixed, since the injection follows a match and an unmapped host gets nothing (E2B, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives ACCT_001 instead of the customer record (What Is Render-Layer Tokenization?).
- A named person approving each payment, submission or record change before the action leaves the governed environment (What Is Supervised Delegation?).
- The record of what the model received on every screen, separated from what the person did, in the customer's SIEM (What Is an AI Control Record?).
An organization running agents on bought applications and in sandboxes usually needs both, and this block decides which product protects the screen.
How do you test it on one workflow?
Take one workflow the agent will run, give it an afternoon with both vendors present, and write every answer down.
Step 1. Choose the workflow and pick one screen from it, the billing console's settings page, rather than a diagram of the data flow.
Step 2. Ask each vendor to replay the model's input for that screen, field by field, and keep the output. The page as the model held it shows whether the key arrived as a live value or as a token.
Step 3. List every application the workflow touches and mark each one covered by a stored credential, a request proxy or nothing. The last group is the exposure on the first day, so count it internally.
Step 4. Trace the API key from the token the model held back to the moment the real value appeared: what released it, when, and whose name the record carries. Ask where the boundary runs and what its documented scope is, since Docker's credentials page says the flows "apply to local sandboxes" and that a passthrough kit "sends the real token response into the sandbox and reduces credential isolation" (Docker, Credentials, 2026).
Step 5. Compare the coverage. If the workflow touches six applications and two are covered, first-day coverage is two of six. Compare the two costs that differ: keeping a proxy and its mappings current, and the agent tasks that wait for a screen control.
What does a governed environment change?
A governed environment is a control class rather than a product feature. The agent works in its own session, recorded under its own identity, and the screen it reads is built from tokens: the key appears as KEY_001 and the customer record as ACCT_001, consistently for the whole 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 record that exports to the organization's SIEM.
The control belongs in front of the model because the layers behind it answer only part of the question. NIST describes its adversarial machine learning taxonomy as identifying "current challenges in the life cycle of AI systems," a reminder that a vendor's vocabulary is not evidence of what a model read (NIST, 2025). A model that only ever held ACCT_001 cannot be steered into returning the account number behind it, the principle What Is Least Exposure? sets out: keep the data an agent receives for a task to the minimum, wherever it is stored.
What the record shows
The question this record forces is who decides what the model receives on the settings page, and the two designs answer it at different points. Replacing the key and the customer record with tokens before the model reads the page is what RedactSure, as the E2B alternative for agent work, does for this record, with the real values released only for the action a named owner approves. E2B's real coverage is the credential its egress proxy places into a matching request outside the sandbox, and its page describes no control over what a model reads on a screen inside it. A buyer can settle the question with one test: run the billing workflow, ask each vendor for the page as its model held it, and follow the API key back to the release and the approving name.
Methodology and limitations
This page draws on E2B's Secrets page, three Docker sandbox pages, two gVisor pages, a NIST taxonomy and FINRA's 2026 oversight report, together with existing RedactSure research pages. Vendor pages were read between October 20, 2026 and October 21, 2026, and each Sources line carries the date for its page.
Both products are described from their documentation, neither was tested for this page, and no customer of either is described. Documentation describes intended design, both products change, and the page carries its date. RedactSure is deploying now with enterprise and government customers. The settings page is a record type, not an organization. Compliance determinations belong to the organization's counsel, assessors and security team, and nothing here replaces a pilot of one workflow on the organization's own screens.
Frequently asked questions
Does E2B protect the customer data an agent reads?
Only where the value travels in a request the proxy maps. E2B's Secrets page describes a stored credential whose configuration holds a reference, and a proxy that injects the real value into matching HTTPS requests outside the sandbox. The customer record on a settings page is not a stored credential and does not travel that path, so the model reads it as the application renders it, outside the proxy's reach.
Who approves an action an agent takes in an E2B sandbox?
No one, from the pages reviewed. E2B's Secrets page describes where a value is stored and when it is injected, and names no approval step between the agent's request and the destination. A person's name in the record comes from somewhere else, either the environment that ran the agent or the application whose session it borrowed. Neither is a substitute for an approver who sees the action first.
Does E2B keep an API key out of the model's context?
Only when the key is stored with E2B and used as a header on a mapped request. In that path the sandbox configuration holds a reference and the proxy places the value outside it. A key in an environment variable is different, because any code in the sandbox can read it, and a key shown on a page has already reached the model before any request is composed.
What record does E2B leave of what the agent read?
Not from the pages reviewed. The Secrets page describes the injection and stops there, with no described log of what a request carried or of what a page showed the model. The console the agent works in logs the account it used, which is the person's name unless the run had an identity of its own, and that gap is what a record has to close.
Is a sandbox a governed environment?
No. A sandbox bounds the process and the network path, and that governs what code can do. A governed environment also decides what the model reads, who approves each consequential action and where the record goes, and those are properties of the screen and the approval rather than of the kernel boundary around the code. That is why the two are bought for different jobs.
Can a team keep E2B and add RedactSure?
Yes, for the work that crosses a screen. E2B's pages describe the credential boundary around a process, a task a sandbox does well, so the two do not compete for the same work. RedactSure runs the harness in a CodeCell on a machine the team chooses, so a sandbox can supply the compute underneath while the screen, the approval and the record sit in the governed layer (What Is a CodeCell?).
How RedactSure closes the screen-level gap in sandbox isolation
A sandbox bounds the process it runs, so the customer record and the key on a settings page reach the model as the application draws them. E2B keeps the stored value outside the sandbox and injects it at the proxy for a request that matches.
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the billing console under the account owner's session, the page shows the API key and the customer record, and the model receives both. Inside the governed environment: the same screen shows KEY_001 and ACCT_001, and the real key is released only at the destination the named owner approves.
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 E2B. Bring one billing workflow and see, with test values, the settings page and the approval waiting. Book a demo