Comparison · RedactSure Research
Chris Sowa · Founder, RedactSure
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RedactSure vs Devin: 2026 Comparison & Alternative
Devin stores a credential in its secrets manager and hands it to the agent, while RedactSure, a Devin alternative built for AI agents, puts a token on the rendered page. 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.
Which Devin alternative decides what a coding agent's model receives when it opens the token page in GitHub settings? RedactSure answers that on the rendered page: the value becomes a consistent token before any model reads it, and the real token resolves only at an approved destination. Devin's secrets manager stores the credential, scopes it, and hands it to the agent to type into a browser page or bind into a shell command, so the agent holds what it uses.
Devin's own secrets page supplies the wording quoted here, alongside GitHub's documentation for the token and its audit log. One record runs through the page: the fine-grained token page in a GitHub organization's settings, where an engineer names a token, sets its expiration and chooses which repositories it may reach. What Is Render-Layer Tokenization? defines the substitution this page tests.
Key findings
- As a Devin alternative for agent work, RedactSure replaces the value on the rendered page with a consistent token before any model reads it, so the agent works with GH_TOKEN_01, the same label on every screen of the run, and the real token resolves only at the approved destination (What Is Render-Layer Tokenization?).
- A model that never receives the token cannot leak it, and commits are where the leak shows: Help Net Security reports "28,649,024 new secrets exposed in public GitHub commits across 2025" (Help Net Security, 2026).
- None of the four scopes Devin lists changes what a page shows: a session credential is "scoped purely to the current session" and still reaches the agent that uses it, which is the value the model works with for the length of the task (Cognition, 2026).
- Devin organizes credentials into organization, personal, repository and session scopes, so a token can be shared by a team, kept to one repository or held for one agent, a flexibility its page describes plainly (Cognition, 2026).
- When the agent works in a browser, "Devin types the value directly," and for shell commands it "binds secrets as environment variables whenever needed" (Cognition, 2026).
- "All secrets are encrypted at rest," which protects the store, and the page does not say what the model receives after the value leaves it (Cognition, 2026).
How do the two compare side by side?
Each row below puts Devin's own wording next to the control-class answer and the check that separates them.
| Dimension | Devin, per its pages | RedactSure | What to verify |
|---|---|---|---|
| Where the control sits | "All secrets are encrypted at rest" in a store that the organization, a repository or a session scopes (Cognition, 2026) | On the rendered page, before any model reads it | Where a value is replaced |
| How coverage starts | A credential added at one of four scopes: organization, personal, repository or session (Cognition, 2026) | The agent works inside the governed environment, and the application is unchanged | How many pages are covered on day one |
| What the model receives | "In the browser, Devin types the value directly" (Cognition, 2026) | A consistent token such as GH_TOKEN_01 on the page | The screen, field by field |
| How real values are restored | The value is bound "as environment variables whenever needed" for a shell command (Cognition, 2026) | Released at an approved destination at the moment of an approved action | Who authorizes the release, and where |
| Who approves an action | A person chooses the scope when the credential is added; the pages describe no approval for the action itself (Cognition, 2026) | A named person approves every payment, submission and record change | A person's name, not a scope setting |
| The audit record | The store records which scope held a value; whether the model saw it is not described on the page (Cognition, 2026) | Every screen as tokens, every action and approval, in a control record exported to the customer's SIEM | Whether the record shows what the model saw |
The two middle columns describe different objects of control. Devin governs the credentials an organization hands an agent: the four scopes decide which value the run may use, and the store keeps it encrypted until the agent types it or binds it. RedactSure governs what the agent reads, and what it leaves behind is a record of the page the model received. The two also differ on who turns a token into a real value: a scope setting on Devin's pages, a named person in RedactSure's design.
What does Devin protect, and where does it act?
Devin's secrets manager does what its page documents: a credential is added at one of four scopes, organization, personal, repository or session, and the session scope ends with the run rather than persisting. Values are encrypted in the store, and the agent can use them in the two ways the page describes: "In the browser, Devin types the value directly," and for shell commands it "binds secrets as environment variables whenever needed" (Cognition, 2026). A team that wants an agent to work with a GitHub token without pasting it into every prompt gets a real store, real scopes and a value it can use.
Every benefit depends on one condition: the agent has to receive the value, because the agent types it or runs the command. The ten-product review includes Devin among the 6 coding agents whose documentation hands the agent a credential in an environment variable it can read; only 2 of the 4 sandboxes keep one out of reach by default (Can AI Coding Agents Read Your API Keys?). The page describes the store and the delivery, and it does not describe a substitution between the store and the model. That is a limit of the design rather than a defect, and the category says as much about itself: "AI agents need local credentials to connect across systems" (GitGuardian, CIO Dive, 2026). A run that ends takes its grant with it, the custody arrangement What Happens to Credentials When an Agent Sandbox Is Destroyed? describes for hosted sessions.
What does an agent read when it opens the token page in GitHub settings?
The record is the fine-grained token page in a GitHub organization's settings: a name field, an expiration, a repository access choice and a list of permissions, and the value the page displays for the token. An agent opens it to make a token for a task, or to check what an existing token can reach before it uses one.
Devin's control covers the store, not this page. A session credential can be typed into a sign-in form when the agent works, but the page that creates a token is drawn by GitHub from its own records, and nothing in the run substitutes the value it displays. GitHub's guidance is to "Treat your access tokens like passwords" and to keep a fine-grained token "limited to only access specific repositories" (GitHub, Tokens, 2026), which governs how a token is made rather than what the model reads once the page shows it. The model receives the page, and the token on it.
There is also an identity gap. The agent works under the engineer's session or a service account. GitHub's security log "lists all actions performed within the last 90 days," and every line names that account rather than the model that read the token (GitHub, Security log, 2026). What Is a Tethered Agent? describes the arrangement, and How Do I Stop a Browser Agent From Seeing the Token It Creates? walks the same page for a token the agent creates.
Which control fits which work?
Keep Devin for
- A credential an agent should use for one session only, because the session scope is "scoped purely to the current session," though the value still reaches the agent for that run (Cognition, 2026).
- Browser work where a page the agent signs in to expects a typed value, as when "Devin types the value directly" (Cognition, 2026).
- Shell work where a command needs the value in its environment, since Devin "binds secrets as environment variables whenever needed," so the process that runs the command inherits it (Cognition, 2026).
Add RedactSure for
- Agents reading screens in applications the organization bought, where the model receives GH_TOKEN_01 instead of the real value (What Is Render-Layer Tokenization?).
- A named person who approves each payment, submission and 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?).
Most teams need both controls, and the split above decides which one covers the screen.
How do you test it on one workflow?
Give both vendors the same afternoon and one real token workflow, and write the answers down as they come.
Step 1. Choose the token page the agent will actually open, the fine-grained token screen in a GitHub organization's settings, rather than a diagram of the credential store.
Step 2. Ask each vendor to replay, field by field, the input its model received for that page, with the output captured; the output shows whether the model saw the token or GH_TOKEN_01.
Step 3. List every application the workflow touches and mark each one as covered by the vendor's control or not; the uncovered ones are the exposure on the first day.
Step 4. Trace one real value, the token or the repository access it carries, back to what released it, when, and whose name is on the record. Ask for the log line rather than a summary, so the release and the approval come from the same record in the same system.
Step 5. Calculate coverage. If the workflow touches five applications and two are covered, first-day coverage is two of five. Compare the two costs that differ: the token work each setup needs, and the agent work delayed until it is done, so both figures sit beside the coverage count and are read together.
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 under its own identity, and it reads a page where values are replaced with consistent tokens before the model sees anything: the token appears as GH_TOKEN_01 and the repository as REPO_001, and the same labels hold 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 page, action and approval is written to a control record that exports to the organization's SIEM.
Research explains why the control belongs in front of the model. Indirect prompt injection gives an attacker a way in through retrieved content: the paper that named it describes attacks that "remotely (without a direct interface)" exploit LLM-integrated applications (Greshake et al., 2023), and drift names the result when injected instructions move an agent off its task (Abdelnabi et al., 2025). CaMeL names the design goal this control class reaches for: "the untrusted data retrieved by the LLM can never impact the program flow" (Debenedetti et al., 2025). A model that only ever read GH_TOKEN_01 cannot be talked into repeating the real token, which is the principle What Is Least Exposure? states: the data an agent receives for a task stays at the minimum.
The environment covers the pages an agent renders in a browser, and it does not govern the terminal, the IDE, the local filesystem, direct API calls or MCP.
What the record shows
Who decides what the model receives when the agent opens the page where the token is created, and whose name is on the record when the real value is released? A render-layer control answers both on the same page: the token becomes GH_TOKEN_01 before the model reads anything, the real value is released only for an approved action, and the release carries the name of the person who approved it, which is the job RedactSure does for this record as the Devin alternative for agent work. Devin's real coverage is the store and the delivery: four scopes, encrypted values, and an agent that types what it holds or binds it to a command. The test fits on one screen: ask each vendor to replay the input its model received for the token page, then trace the real token back to the action that released it and the person whose name is on it.
Methodology and limitations
This page draws on Devin's secrets page, two GitHub documentation pages, three research papers, a press report on the 2026 GitGuardian state of secrets sprawl and existing RedactSure research pages. Vendor pages were read as of October 21, 2026, and each Sources line carries the date for its page. Vendor statements are quoted in their own wording, and 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 a behavior, it refers to the pages reviewed for that product.
The products on this page are described from documentation; none was tested for this page, and no customer of either product 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 token page is an illustrative record type. Compliance determinations belong to the organization's counsel, assessors and security team, and nothing here replaces a pilot of one workflow on its own screens.
Frequently asked questions
Does Devin's secrets manager protect what an agent reads on a screen?
No, not the screen. Devin's page describes a store with four scopes and two ways for the agent to use a value: typing it into a browser page, and binding it as an environment variable for a shell command. Both deliver the value to the agent, because using it is the agent's job. What a page in another application displays is outside that store, and the pages reviewed describe no substitution there.
Who approves the agent's action when Devin holds the credential?
A person approves the credential's scope, not the action. Someone adds the value at organization, personal, repository or session scope, and the agent then uses it as it works. The page describes no approval step attached to a particular payment, submission or record change. That difference matters when the agent acts in a customer system: the scope says what value it may hold, and a named approval says what it may finish.
What record exists of what the model read?
Not from Devin's pages. The store records which scope holds a credential, and a session credential ends with the run, but the page does not describe a log of what the model received on a screen. GitHub's security log covers the actions a token takes for 90 days and names the account whose session was used (GitHub, Security log, 2026). A record that answers the question has to come from the environment the agent worked in.
Does a session-scoped credential keep the value away from the model?
Only for later runs. A session credential is "scoped purely to the current session" and is not saved for future sessions (Cognition, 2026), which limits how long the value lives in the store. It does not change what happens during the session: the agent receives the value to type it or bind it, so the model works with the real token for the length of the task. The scope controls the lifetime of the value, not what the model sees.
Is a GitHub token a fair test of the difference?
Yes, because the token is created on a page and then used by an agent. GitHub's guidance is to treat a token like a password and to keep a fine-grained token limited to the repositories it needs (GitHub, Tokens, 2026), which is sound practice for the token itself. The page that displays a new token still renders it, and the model reading that page receives it.
Should a team replace Devin to protect a GitHub token?
No. A team that runs Devin needs a place to keep the credentials the agent uses, and a secrets manager does that job. What it does not do is decide what the model reads on a page the agent opens in another application. Most teams need both controls, and the choice is which product covers the screen.
How RedactSure closes the gap between the store and the screen
Devin's control covers the credential in its store and the moment the agent receives it, and the token page the agent opens sits outside that store. The exposure is measured: Help Net Security reports "28,649,024 new secrets exposed in public GitHub commits across 2025."
The environment that enforces this is built by RedactSure, an AI agent controls, governance and data protection company.
Before: the agent opens the token page under the engineer's session, the fine-grained token renders in full, and the model receives it. Inside the governed environment: the same page shows GH_TOKEN_01, and the real token is released to GitHub's API only when the named engineer approves the request.
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 Devin. Bring one token workflow and see, with test values, what the model reads and which approval releases the real token. Book a demo