---
type: Article
title: Demystifying the (In)Security of OAuth-based Account Linking in Connector Ecosystems
description: Project page for a systematic study of OAuth connector account linking. It links the paper analyzing cross-user session fixation and connector or tenant confusion, alongside an Android static-analysis screening method and deployment validation. Earlier attack disclosures are distinguished from the later measurement study.
resource: "https://mobitec.ie.cuhk.edu.hk/connector-oauth-security/"
tags: [article, webseclist-reference, the-chinese-university-of-hong-kong, oauth, identity, session-fixation, static-analysis, measurement-study, owasp-a07-2021]
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resource: "https://mobitec.ie.cuhk.edu.hk/connector-oauth-security/"
title: Demystifying the (In)Security of OAuth-based Account Linking in Connector Ecosystems
author: Kaixuan Luo, Xianbo Wang, Pui Ho Adonis Fung, Wing Cheong Lau
also_at:
- "https://mobitec.ie.cuhk.edu.hk/connector-oauth-security/paper.pdf"
authors:
- Kaixuan Luo
- Xianbo Wang
- Pui Ho Adonis Fung
- Wing Cheong Lau
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original_url: "https://mobitec.ie.cuhk.edu.hk/connector-oauth-security/"
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---
# Demystifying the (In)Security of OAuth-based Account Linking in Connector Ecosystems
**Demystifying the (In)Security of OAuth-based Account Linking in Connector Ecosystems** - Kaixuan Luo, Xianbo Wang, Pui Ho Adonis Fung, Wing Cheong Lau, The Chinese University of Hong Kong.
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Demystifying the (In)Security of OAuth-based Account Linking
in Connector Ecosystems
Kaixuan Luo† , Xianbo Wang† , Pui Ho Adonis Fung‡ , Wing Cheong Lau†
† The Chinese University of Hong Kong ‡ Samsung Research America
Abstract—Modern productivity apps, automation platforms, Connector- Integration
equipped Apps Platforms Connectors
and AI agents orchestrate across external tools through cloud- Microsoft
(a.k.a. Tools,
Power Automate Services, Integrations)
based “connectors”. To obtain authorized access to connector
Notion
accounts, these applications rely extensively on the OAuth 2.0
protocol. However, tracking authorization context across web Agentic AI Infrastructures
origins and user-agents, while maintaining the binding to the Microsoft
Copilot Studio
applications’ own user identities (i.e., a secure Account Link- Amazon
Bedrock AgentCore
ing process), pushes OAuth beyond its original client–server Build
Custom AI Agents
model assumptions. The rise of the OAuth-as-a-Service (OaaS)
……
paradigm further complicates trust boundaries in OAuth.
In this paper, we present the first comprehensive study
Figure 1. Connector Ecosystems. With OAuth 2.0, users can delegate access
of OAuth-based account (mis)linking in connector ecosystems. to connectors to various types of applications, such as connector-equipped
By systematizing real-world account linking architectural pat- apps, integration platforms, and AI agents. These applications can then
terns, we show how “OAuth connections”, commonly intro- invoke the connectors to perform tasks on behalf of users.
duced to manage account linking, can inadvertently break ses-
sion integrity and security boundaries in OAuth. This enables paradigm, where a centralized “Token Vault” [3], [4] handles
multiple forms of connector account takeovers.
OAuth token retrieval and storage for multiple AI agents.
In the aforementioned ecosystems, each external service
We develop OASIS (OAuth Session Integrity Scanner), an
integration, with its OAuth configurations, API endpoints
analysis framework that identifies account linking implemen-
(a.k.a. Resource Servers), and wrapper functions for API
tations and detects novel Cross-user OAuth session fixation
calls, is encapsulated as a “connector”. Collectively, these
(COSF) vulnerabilities in mobile apps. Our empirical anal-
OAuth-enabled settings define what we term the connector
ysis discovers 40 vendors susceptible to COSF and identifies
ecosystems (Fig. 1). However, applying OAuth securely in
additional Cross-tenant confused deputy threats in 8 OaaS
this context is non-trivial: OAuth architectures have evolved
providers. We propose practical countermeasures that have from simple client–server models into complex patterns
since been adopted by major vendors such as Amazon Bedrock executing flows across disparate web origins and user-agents
AgentCore. We lead ongoing discussions and standardization (UAs), and even into multi-tenant architectures as AI agents
efforts to update OAuth security best practices in the IETF. offload OAuth responsibilities to OaaS providers.
The Missing Piece of OAuth Authorization. Prior
1. Introduction OAuth research [5], [6], [7], [8] has primarily focused on tra-
ditional applications with simple client–server architectures.
Connector Ecosystem. Modern software systems are As illustrated in Fig. 2, OAuth at the protocol level concerns
transforming how applications (apps) interact with external how an application (OAuth client) obtains an end-user’s
tools on behalf of users. Productivity apps such as Evernote access token from an authorization server (AS), treating
integrate with SaaS services like Outlook Calendar to sync the application as a single logical entity. However, OAuth
user data across clouds. Integration platforms [1] such as remains agnostic to the “authorization context”, regarding
Microsoft Power Automate, IFTTT, Amazon Alexa, and how, in a multi-user application, the obtained access token
Google Home enable broader automation with a portfolio from an AS should be associated with the app’s own user
of services. OAuth 2.0 [2] has been the predominant proto- identity (i.e., “Account Linking”).
col for delegated authorization, allowing end-users to grant Once this dimension is taken into account, critical
applications access to the services without password sharing. ambiguities emerge. While existing OAuth standards [2],
The emergence of Agentic AI has accelerated this [9] adequately handle same-origin and same-UA scenarios,
trend. Developers can now build autonomous agents through challenges arise when the application’s user session is main-
infrastructures such as Microsoft Copilot Studio, Ama- tained in a different environment from the OAuth client, such
zon Bedrock AgentCore, and Composio. These agentic as on a distinct origin (in web apps), a separate UA (in native
AI infrastructures introduce the OAuth-as-a-Service (OaaS) apps), or under a different entity (as in OaaS architectures).
1
Textbook OAuth: to COSF. It further enables cross-tenant attacks, in which a
access token
RFC6749 - OAuth Framework
intended for the app malicious agent can compromise authorizations of agents in
RFC8252 - OAuth for Native Apps Web/Native App Authorization
as OAuth Client Server (AS) other tenants. These include two confused deputy-style [13]
This Paper: attacks, Cross-tenant Client ID Confusion and Cross-tenant
OAuth-based Account Linking COAT (Cross-connector OAuth Account Takeover), which
in Connector Ecosystems
exploit the blurred trust boundaries between tenants, and
between both tenants and connectors, respectively.
proprietary access token
"OAuth Connection" intended for an app user Security Impact. In many cases, a single hyperlink click
Web/Native App OAuth Client Authorization
Focus ➊:
self-managed managed by Server (AS) is the only interaction needed to compromise a user. These
by the app or an external entity (Connector)
Multi-user Application attacks enable account takeovers, granting attackers unau-
Focus ➋:
Decoupled Relationship thorized access to the connected services. The same exploit
can target any connector in a vulnerable application, or that
Figure 2. Textbook OAuth vs. Account Linking. Textbook OAuth standard- within any tenant of a vulnerable OaaS provider.
izes token negotiation for an application (OAuth client) but is agnostic to
its user session management. Account Linking further specifies how an app Vulnerability Detection. To facilitate our analysis, we
associates a token with the app’s user identity. Notably, the app’s core busi- develop OASIS (OAuth Session Integrity Scanner), a static
ness logic (where user session resides) is often decoupled from its OAuth analysis framework that identifies account linking imple-
client component. Account Linking is prevalent in connector ecosystems. mentations and detects COSF vulnerabilities in Android
apps using an exclusion-based approach. OASIS identified 12
Notably, existing mechanisms like state parameter binding apps supporting account linking and, in an extended dataset,
[2, §10.12] are underspecified regarding end-to-end session detected 20 vulnerable apps with high accuracy.
integrity in such cases. Measurement Study. Beyond mobile apps, our broader
Our Study. In this paper, we conduct a systematic investigation, combining OASIS-backed scans with a cu-
examination of OAuth architectural patterns in connector rated set of leading vendors, reveals industry-wide threats:
ecosystems and their security implications. We reveal how 1) COSF vulnerabilities in 19 connector-equipped apps and
implementation details left underspecified by the OAuth 15 integration platforms, including top vendors such as
protocol play a critical role in accurately and securely Slack, Alexa, n8n [14], IFTTT, Perplexity, and Manus. 2) 19
modeling account linking flows. At its core, we observe that instances of cross-user or cross-tenant vulnerabilities across
OAuth clients often introduce an abstract OAuth connection 8 agentic AI infrastructures, including Amazon Bedrock
to manage a token throughout its lifecycle: AgentCore [3], Microsoft Copilot Studio, and Composio.
1) It governs token retrieval as an authorization session in Responsible Disclosure. To date, we have received ac-
OAuth flows (i.e., an OAuth session). When user sessions knowledgments from 20 vendors, with over 15 confirmed
in the UA are inaccessible, applications often resort to fixes and a total of $35,850 in bug bounties. Drawing on this
OAuth sessions, passed via URLs, to identify end-users. experience, we distill a set of countermeasures, ranging from
2) It serves as a persistent handle for internal reference to short-term mitigations to long-term architectural defenses,
the token, such as for API calls and token refresh. and lead ongoing standardization efforts to update OAuth
Conceptually, an OAuth connection can be characterized security best practices in the IETF, ensuring the safe deploy-
by three key elements that form its authorization context: ment of OAuth in rapidly evolving connector ecosystems.
, representing the app’s user iden- Contributions. Our main contributions are as follows1 :
tity, the tenant (in OaaS), and the connector involved. • We demystify OAuth architectural patterns and security
Attacks. The gap between the authorization context challenges not captured by textbook OAuth (§2) or related
tracked by OAuth connections and those enforced in OAuth work (§8), but fundamental to connector ecosystems (§3).
flows exposes critical vulnerabilities absent under standard • We present Cross-user OAuth Session Fixation (COSF), a
OAuth assumptions. Table 1 summarizes our threat analysis. new class of OAuth attack prevalent in Account Linking,
Cross-user Attacks. Cross-user OAuth Session Fixation and propose comprehensive defenses (§4). We further ex-
(COSF) arises when an OAuth session is used to com- tend the analysis to Cross-tenant confused deputy threats
plete an OAuth flow without verifying its binding to the in OAuth-as-a-Service environments (§5).
initiating user’s identity. An attacker can pre-establish (fix- • We develop OASIS, a framework for identifying account
ate) a controlled OAuth session and trick a victim into linking support and detecting COSF vulnerabilities in
completing authorization; the resulting token, carrying the mobile apps (§6).
victim’s connector access, is then linked to the attacker’s app
• We uncovered vulnerabilities across 42 vendors through
account. Unlike traditional web session fixation [10], [11],
our measurement study (§7).
[12], which hijacks user sessions through unauthenticated
• We actively engaged in responsible disclosure and are
session IDs, COSF exploits OAuth sessions derived from
existing user sessions to hijack subsequent authorizations. working on updates to OAuth security best practices in
the IETF [16].
Cross-tenant Attacks. The threat landscape expands fur-
ther under OaaS. As a single “Token Vault” serves multiple, 1. We publicly release the artifacts, including the experimental dataset,
potentially untrusted applications (agents) across diverse ori- source code of OASIS, and attack demo videos, on our project website [15]:
gins and UAs, the OaaS architecture is inherently susceptible https://mobitec.ie.cuhk.edu.hk/connector-oauth-security.
2
Table 1. C OMPREHENSIVE OAUTH T HREAT E NUMERATION IN “C ONNECTOR E COSYSTEMS ”. T HESE ECOSYSTEMS INTRODUCE AN ABSTRACT
“OAUTH C ONNECTION ” TO MANAGE ACCOUNT L INKING , WHICH TRACKS THE AUTHORIZATION CONTEXT AS A TUPLE OF .
Potential Account Mislinking Threats
OAuth Connection’s Cross-user Cross-tenant Cross-connector
Category [§3.1] OAuth Client Authorization Context: OAuth Session Fixation [§4.1] Client ID Confusion [§5.1] OAuth Account Takeover (COAT)
a b
Defense: User Session Binding Defense: Tenant Scoping Defense: Connector Distinctionc
Connector-equipped Apps Self-managed (Cross-Origin/UA) (No untrusted connector)
Integration Platforms Self-managed (Cross-Origin/UA) (Single-tenant) COAT [1]
Agentic AI Infrastructures Managed (Separate Responsibilities) Cross-tenant COAT [§5.2]
Notation: indicates the threat is applicable; indicates the threat is not applicable.
a
User Session Binding: User that Starts OAuth == User that Completes OAuth, enforced via session integrity checks at the original origin or UA.
b
Tenant Scoping: Tenant that User Consents == Tenant that Receives Access, enforced via per-tenant OAuth client registration.
c
Connector Distinction: Connector that Starts OAuth == Connector that Completes OAuth, enforced via globally unique per-connector redirect_uri.
Application Browser Connector a client_id. At step 4 , the AS can further authenti-
cate the client using a credential, typically a shared se-
cret (i.e., client_secret). The process of negotiating such
OAuth Client User-agent (UA) Authorization Server (AS) identifiers and credentials prior to OAuth flows is called
➊ Start OAuth
user session client registration. A web app running on a backend server
➋ /authorize?client_id=client-AS&state=state can securely store secrets and is therefore referred to as
&redirect_uri=/callback a confidential client. In contrast, native apps that store
Authorize
➌ /callback?state=state&code=code credentials on-device cannot maintain their confidentiality
Cookies: user session and are treated as public clients.
➍ /token with code Code OAuth Session Integrity. In this work, we define OAuth
linked to an app user
➎ access token
Exchange session integrity based on [5], as the property that a user
Figure 3. OAuth 2.0 Authorization Code Grant Flow who initiates an OAuth flow must be the same user
who completes OAuth. To date, Cross-site Request Forgery
2. Background: Textbook OAuth (CSRF) is the most widely-discussed session integrity threat
in OAuth. According to RFC requirements [2, §10.12]
OAuth Authorization Code Grant. The textbook OAuth and [17, §5.3.5], the OAuth state parameter, an opaque
flow (Fig. 3) follows a “three-legged” design, as it involves value sent in the authorization request and returned un-
three entities: an OAuth client hosted by the application in changed in the authorization response should be bound to
need of tokens; a user-agent (UA) for end-user interactions, the UA session. Without proper validation, an attacker can
typically a web browser; and an authorization server (AS), inject an auth code into a victim’s unsolicited OAuth flow
from which the application obtains access tokens. As a in step 3 , thereby breaking session integrity and allowing
running example, a web app (e.g., an online PDF editor) the victim to access attacker’s resources (i.e., Login CSRF).
may request access to a user’s private files in a cloud storage
service (e.g., Dropbox), where the service runs an AS. 3. Understanding Account Linking
An OAuth flow consists of two phases: authorization and
code exchange. The authorization phase would issue a short- This section demystifies account linking in connector
lived authorization code (auth code): 1 The user initiates ecosystems, examining the architectural patterns that enable
OAuth via the UA, which sends a request to the web app’s it and the implementation challenges that make it non-trivial.
backend (hereafter, the OAuth initiation request). 2 The For ease of understanding, Table 2 provides a mapping
user is then redirected to the AS in an authorization request, between standard OAuth roles and common industry jargon.
prompted to log in at the storage service’s website and grant For example, we use the umbrella term connector to denote
authorization consent. Note that explicit consent may be the entity that plays the AS role in OAuth.
skipped if prior consent exists, making the authorization an
automatic process. 3 An auth code is issued by the AS in an 3.1. Connector Ecosystems
authorization response, passed through the UA, and handed
to the web app’s backend. It reaches the callback (a.k.a. In ecosystems such as application integration [18], [19]
redirection) endpoint, as specified by the redirect_uri and agentic AI [20], each external service integration is
parameter (redirection URI) in the earlier request. encapsulated as a connector. Applications perform OAuth-
In the code exchange phase, the OAuth client at web based account linking and maintain a persistent “OAuth
app’s backend exchanges the auth code for an access token connection” to that service. This allows applications to
via a server-to-server request to the AS (token request 4 perform tasks on behalf of users with authorized access. We
and response 5 ). Eventually, the access token is associated scope our study to three representative product categories:
with the web app, which can then call the service’s APIs to Integration Platforms. Cloud-based integration platforms
retrieve protected resources such as the user’s private files. orchestrate interactions across multiple connectors from an
OAuth Client Registration and Client Types. At steps open marketplace, often in a low-code or no-code fashion.
1 and 4 , the AS can uniquely identify the client using Following prior work [1], we examine 3 major types of
3
Table 2. T ERMINOLOGY M APPING TABLE at runtime. In certain cases (e.g., agents as customer service
chatbots), the concept of an app account may extend to
OAuth Roles [RFC6749] Industry Jargon
Authorization Server (AS)
cover an anonymous session, which we subsume under “user
Connector (e.g., Dropbox)
& Resource Server (RS) session”. Depending on the use case, OAuth tokens may be
Application (App)
- Connector-equipped App (e.g., Evernote);
- Integration Platform (e.g., Amazon Alexa);
either linked to the app account for long-term access, or
subsumed under - Agents deployed with Agentic AI Infrastructure (e.g., with valid for the lifetime of the current user session.
OAuth Client Amazon Bedrock AgentCore): the OAuth-as-a-Service paradigm.
Concrete form as a web or native application. Textbook OAuth: Track by Session. Revisiting the text-
OAuth Client
- A Backend Component of Connector-equipped App/Integration Platform; book OAuth flow, the OAuth client may rely on the applica-
- “Token Vault” in Agentic AI Infrastructure.
tion’s user session stored in the browser for account linking.
Resource Owner Connector Account of the end-user (e.g., Dropbox account)
Not Modeled App Account of the end-user (e.g., Amazon Alexa account)
Yet, the dotted steps in Fig. 3 are outside the scope of the
Tenant. Definition: A tenant is an organization signing up OAuth protocol, namely, how OAuth is initiated and how the
Not Modeled at OaaS to develop custom agent(s) paired with connectors,
deploying the agent(s) in its own trust domains for its own end-users.
application identifies which user should receive the tokens.
Reflecting on Fig. 2, this gap exists because
RFC6749 [2] only specifies “first-order OAuth”, regarding
platforms, including workflow automation platforms, virtual how an application obtains OAuth tokens from an end-
assistants, and smart homes. user (i.e., the resource owner). Account linking, however,
Connector-equipped Apps. Applications such as Evernote represents “second-order OAuth”: an application’s own user
do not fit neatly into common integration platform types, yet needs tokens from the same user. Textbook OAuth overlooks
they have specific integration needs. For instance, Evernote this distinction because it typically assumes a same-origin,
supports calendar synchronization through Google and Out- same-UA deployment, where the application and its
look Calendar integrations. We refer to such apps with a few OAuth client are deployed in a single origin and UA, and
purpose-specific connectors as connector-equipped apps. therefore the UA (web browser) naturally preserves the
Agentic AI Infrastructures. Emerging platforms such as user session at the callback endpoint. In more complex
Amazon Bedrock AgentCore provide infrastructures for architectures where the application and its OAuth client are
building AI agents that integrate with connectors. Histori- decoupled components, this assumption no longer holds.
cally, niche infrastructure-level solutions have existed in the To better reflect this decoupling, we hereafter use the term
form of Integration Platform as a Service (iPaaS) and mod- OAuth client to refer specifically to the component that
ern API Management Service / API gateway. By contrast, handles OAuth responsibilities of the application, and the
such infrastructures have become pivotal in agentic AI: term application to refer to its general business logic (e.g.,
AI agents often need to accommodate customized enter- user session management).
prise and organizational requirements, and therefore vendors
position themselves as Agent Builders or AI Gateways to
3.3. Decoupled OAuth Architectural Patterns
support the development of custom AI agents. End-users
interact with agents across disparate trust domains rather Modern OAuth deployments often violate textbook
than through a centralized integration platform. A typical OAuth assumptions to support account linking across web
offering includes a software development kit (SDK) and de- origins, UAs, and security boundaries. Such decoupled
veloper console for building agents and equipping them with OAuth architectural patterns create three key challenges:
pre-built or custom connectors. Agent developers rely on Challenge 1: Cross-Origin Session Tracking. When
the OAuth client (so-called “Token Vault”) provided by the account linking spans multiple origins in a web applica-
infrastructure for token retrieval and lifecycle management. tion (see Fig. 4), for instance, account linking initiated at
From an OAuth perspective, this has led to a new busi- origin A but with the OAuth callback handled by origin B,
ness model, OAuth-as-a-Service (OaaS), where OAuth client origin B cannot determine which user the received autho-
responsibilities are effectively outsourced to a centralized rization should be associated with. This occurs because the
entity. This also shifts OAuth from the traditional single- user session at origin A is not accessible to origin B due
tenant model, where each OAuth client serves a single to same-origin policy [21] (or more precisely, due to site
application, to a multi-tenant architecture in which a ten- isolation at the registrable domain level, i.e., eTLD+1 [22]).
ant corresponds to one or more agents built by the same This situation is common in modern deployments where
organization’s developers. server-side components are decoupled, such as a shift from
monolithic to microservices architecture.
3.2. Account Linking: Second-order OAuth Challenge 2: Cross-UA Session Tracking. As depicted
in Fig. 5, when a native app (e.g., an Android mobile app)
Following the definition in [1] (with aligned terminol- supports account linking and follows RFC8252 [9] to use an
ogy), we define Account Linking as the process of con- external UA (web browser) to handle OAuth, it launches the
necting a user’s connector account to their app account. browser to request authorization for the connector. However,
Access to the connector account is represented by the OAuth due to process isolation, the native app cannot share the user
access token (and/or refresh token [2, §6]), while the app session with the browser, thereby breaking session tracking
account reflects the user’s identity within a multi-user appli- between the two UAs and creating a session gap at the
cation, typically represented by an authenticated user session OAuth callback. To date, OAuth specifications lack guidance
4
App Backend Connector Authorization
(OAuth Client) (AS) Applications OAuth Client Server (AS)
Tenants Token Vault Connectors
Start OAuth (Agents)
user session
App origin A
/authorize?state=state&redirect_uri=originB
Backend
Components
Authorize user_id OAuth Connection
(Servers)
App origin B
Users =
New origin,
Frontend
No user session Components user
session
(UAs)
Figure 4. Challenge in Cross-Origin OAuth: Server-side decoupling sep- Channels
arates application components. However, the browser cannot track user
session across origins due to Same-origin policy (SOP) and site isolation. Figure 6. OAuth-as-a-Service in Agentic AI Infrastructures: Agents can be
deployed in any channels, crossing origins and UAs by design.
App Backend Connector
(OAuth Client) User-agent A User-agent B (AS)
Native App Web
Browser
Start OAuth
user session
/authorize?state=state&redirect_uri=app_backend
Authorize
New user-agent,
No user session
Figure 5. Challenge in Cross-UA OAuth: Native apps follow RFC8252 to
perform OAuth in an external UA (browser). However, the browser cannot Figure 7. Channels for Publishing an Agent in Microsoft Copilot Studio
track the native app’s user session due to process isolation.
• From the application’s perspective, upon receiving a
for native apps acting as confidential clients. RFC8252 [9] user’s request to initiate OAuth, it queries the OAuth client
only covers native apps as public clients. Yet, during account to generate an authorization URL, returns it to the user,
linking, a native app behaves more like a UA, with its OAuth and waits for the OAuth client to obtain the token. After
client implemented in the backend as a confidential client. OAuth completes, the app may access protected APIs in
Challenge 3: Outsourced OAuth Responsibilities in one of two methods: (1) typically by calling the OAuth
OaaS. Custom AI agents (applications) outsource OAuth client, which acts as an API gateway that routes requests
responsibilities to the OaaS, where its “Token Vault” acts to the appropriate connector’s APIs with the correct token
as an OAuth confidential client to negotiate OAuth tokens attached, or (2) less commonly by retrieving the raw
with the connector’s AS, and securely stores them for the access token from the OAuth client, allowing the app to
agents. Agents typically authenticate to the Token Vault us- invoke the APIs directly, as seen in some OaaS providers.
ing per-tenant API keys [23] or per-agent workload identity • From the OAuth client’s perspective, it needs to fulfill
tokens [24], [25] to retrieve the tokens or make API calls, the application’s request to complete OAuth flows, while
thereby avoiding the complexity of implementing OAuth keeping track of the context in which the application
client logic and token management themselves. requests authorization.
As illustrated in Fig. 6, agents that rely on OaaS inher- • From the end-user’s perspective, the user experience
ently cross origins and/or UAs, since their main business should be consistent with textbook OAuth. The pro-
logic (including user sessions) remains in the tenants’ own prietary details between the application and decoupled
web origins or native apps, whereas the OAuth callback is OAuth client should be opaque to users.
operated by the Token Vault. This situation is further com-
plicated by the heterogeneous agent publishing channels: 3.4. OAuth Connection
To interact directly with end-users, agents may be deployed
across various environments, ranging from web/native apps To coordinate between the application and the OAuth
to bots within instant messaging (IM) software such as client, vendors commonly introduce the abstract notion of
WhatsApp and Telegram (see Fig. 7). While web and native an OAuth connection, which uniquely identifies each OAuth
apps are fully controlled by the agent developer, IM channels token together with its authorization context in account
depend on external application contexts, compounding the linking. While a token represents access to a protected
session tracking challenge. Consequently, a session gap resource, the OAuth connection manages an application’s
exists not only between the Token Vault and the agent, but access to that token throughout its lifecycle. To identify the
may also independently exist between the agent’s backend authorization context, each OAuth connection is associated
and its channel (the UA running its frontend). with certain metadata. Formally, we define the authorization
Expectations. Despite these challenges, decoupled OAuth context of an OAuth connection as a tuple:
deployments should uphold the following expectations: OAuth connection = .
5
Start OAuth
user session Start OAuth
App origin A
302 redirect user session
user session -> OAuth session /authorize?state=state&redirect_uri=app_backend
ID=< id>
session
thorize? user session -> OAuth session
/pre_au Authorize
App origin B /authorize?state=state&redirect_uri=originB Retrieve OAuth session from state
Set-Cookie: sessionID ...
Authorize
... OAuth session Figure 9. OAuth Session in the state parameter
Figure 8. OAuth Session as a standalone parameter in URL
3.6. Threat Model
At a minimum, the OAuth client should track the recip-
ient user of the token, and may also track the current con- Our study considers two threat models that build upon
nector or tenant if it supports multiple connectors or tenants. the web attacker model [27], [28]. They capture two realistic
An end-user may also configure multiple OAuth connections ways in which an untrusted component can infiltrate connec-
for the same connector at a tenant (e.g., to manage multiple tor ecosystems: either as an application’s end-user, or as a
Gmail accounts), in which case additional distinguishing developer (via an OaaS tenant). This enables five new types
metadata may be included, keyed by a unique connection ID. of attacks spanning two classes (cross-user and cross-tenant
OAuth connection is used both during OAuth flows and attacks) within connector ecosystems. In both models, the
for token management afterward. (1) During an OAuth flow, victim is an honest user of a benign application. These at-
the OAuth connection is instantiated as an authorization tacks do not require an active user session of the application
session (hereafter, OAuth session), which allows the appli- in the victim’s browser; however, an existing user session
cation to track the connection in the user’s browser. OAuth on the connector side can enhance attack stealthiness.
session is derived from and maintained independently of Basic Model: Untrusted User (Three Cross-user Attacks
the application’s user session. (2) After OAuth completion, in §4).
the OAuth connection serves as the handle to reference the • Attacker Capabilities. The attacker is a regular user of a
obtained token, such as in token refresh and API calls. benign application with no special privileges.
• Attack Scenario and Goal. The attack occurs in a cross-
3.5. Common (but Flawed) Designs user scenario and typically involves the victim clicking a
crafted link provided by the attacker (§4.1, §4.2.1). By
In practice, we observe two common implementation doing so, the attacker can hijack access to the victim’s
patterns for tracking OAuth connections in OAuth flows: connector by linking it to attacker’s app account. Some
embedding an OAuth session identifier (OAuth sessionID) variants (§4.2.2) require no user interaction: the attacker
in the URL, either as a standalone, client-defined parameter, can forcibly bind their connector account to the victim’s
or within the OAuth state parameter. app account, causing victim to use attacker’s resources.
OAuth Session in standalone URL parameter. A com- Extended Model: Untrusted Tenant (Two Cross-tenant
mon pattern inserts an additional request between the OAuth Attacks in §5). Under OaaS, tenants that are otherwise
initiation request and the authorization request. This addi- well-isolated may lack isolation at the OAuth protocol level.
tional pre-authorization request carries the OAuth sessionID Tenants reflect a realistic organizational security boundary:
as a URL parameter to transfer session information from • Attacker Capabilities. An attacker can freely sign up for
origin A to origin B, or from a native app to a web browser. the OaaS to set up a malicious tenant.
As an example, in a cross-origin scenario, when the server at • Attack Scenario and Goal. A malicious tenant can trick
origin B receives the pre-authorization request, it redirects the victim into interacting with a connector associated
the user to the authorization endpoint and either sets the with the attacker’s application. This poses cross-tenant
OAuth session in the browser (e.g., via Set-Cookie [26], as threats, where the victim’s connector access in a benign
illustrated in Fig. 8), or continues carrying the session value tenant can be compromised by the malicious tenant.
in the URL (i.e., via the state parameter).
OAuth Session in state parameter. An alternative de- 4. Cross-user Attacks
sign embeds the OAuth session identifier directly into the
state parameter. As an example, Fig. 9 shows such a design The victim completes an OAuth flow, but may not be the
under cross-UA setting. This approach is appealing because, one who initiated it. Crucially, under the common design
per OAuth specification [2, §4.1.1], the state parameter is patterns in §3.5, the initiator of the OAuth flow is the user
intended to maintain state during the authorization phase. to whom the authorization is linked. Consequently, if a
Unfortunately, the above common designs are also inher- malicious user initiates an OAuth flow that a victim later
ently insecure. They allow the OAuth session to be fixated completes, the victim’s connector account would be linked
within any UA, exposed to any origin, and propagated into to the attacker’s app account. We refer to such account mis-
the OAuth callback, which introduces serious security risks. linking issues in cross-user settings as Cross-user Attacks.
6
attacker's
Browser / Native App
victim's
Browser
takeovers. For example, the attacker compromises the vic-
tim’s Dropbox connector, then the attacker is able to access
/ the victim’s Dropbox files directly from the attacker’s app
➊Start OAuth Key Step:
account. Moreover, since the weakness lies in the OAuth
client, which serves all connectors as a single, shared entity:
Generate
OAuth session ➋ Share URL of • In connector-equipped apps, although only a handful
/pre_authorize or /authorize
=
➌ /pre_authorize ➌ /authorize of connectors are supported, all of them are at risk.
• In integration platforms, all connectors in the plat-
Retrieve ➍ /callback with codevictim Authorize
form’s marketplace are equally affected.
OAuth session
➎ /token with codevictim
=
Code • In agentic AI infrastructures, vulnerabilities extend to
➏App
Exchange
attacker's victim's tokenvictim all tenants and every connector used by their agents.
Account Connector Account
Consequently, as long as the victim is an end-user at any
Figure 10. Attack Flow of Cross-user OAuth Session Fixation (COSF)
of the affected vendors, they risk having their Dropbox
4.1. Cross-user OAuth Session Fixation (COSF) connector access taken over, facilitating targeted attacks.
One-click Attacks. Connectors such as GitHub, Dropbox,
4.1.1. Attack Flow. In a COSF attack, the attacker fixates Outlook Calendar, and OneDrive support silent/automatic
an OAuth session in the victim’s browser to hijack the authorization. This means that when prior consent is in
connector access. Assume the victim has previously linked place (i.e., if the victim user has previously connected
the targeted connector account to their app account and that these connectors with the application under a pre-configured
a valid session for the connector account exists in victim’s client_id), no explicit consent would be required for an-
browser. The attack steps are illustrated in Fig. 10, and other linkage, enabling stealthy, one-click attacks.
outlined as follows: Practical Consent Phishing. For connectors that always
1 The attacker initiates account linking with the tar- require explicit consent or for first-time authorizations, the
geted connector via the application. threat remains and still constitutes a valid attack. This is be-
Variant 1: The attacker records the pre-authorization cause the victim has no way of knowing that their connector
request URL (e.g., https://client.com/pre_authorize account would be linked to the attacker’s app account rather
?sessionID=7dpf1jhpq4q3s5fnj0hts1oou8), where the than their own. The OAuth consent screen presents the token
sessionID value is the OAuth session identifier derived recipient as a trusted entity (which is the app itself, e.g.,
from the attacker’s app identity. Amazon Alexa), making these attacks more convincing than
Variant 2: The attacker records the authorization request conventional consent phishing campaigns in OAuth [29].
URL (e.g., https://connector.com/authorize?client_ Attack Comparison. In classical web session fixa-
id=&redirect_uri=https://cli tion [10], [11], [12], an attacker fixates a session identifier
ent.com/callback&state=7dpf1jhpq4q3s5fnj0hts1oou in the victim’s browser to hijack their user session. In
8), where the state encodes the OAuth session. Cross-user OAuth Session Fixation, the attacker fixates
2 The attacker shares the pre-authorization request URL an OAuth session identifier derived from the established
(Variant 1) or the authorization request URL (Variant 2) user session to hijack the victim’s connector access.
with the victim as a hyperlink.
3 When the victim clicks the link, their browser would 4.2. COSF-related Implementation Flaws
be redirected to the app’s authorization endpoint (Variant 1)
or would directly visit it (Variant 2). This section discusses two implementation issues in
4 If prior consent exists, the access is granted automat- account linking that rely on COSF, where OAuth sessions
ically, with code and state sent back to the app’s OAuth either jeopardize the app’s user sessions or are guessable.
callback. While some cookies may be attached, the app
backend only consumes the cookies used to maintain the 4.2.1. Login CSRF of App Account. When the OAuth
OAuth session and/or to validate state; the app’s session session is initially embedded in a standalone URL parameter
cookies are not available or not used to verify user identity. (§3.5), we noted that a dedicated session cookie is typically
5 The app’s OAuth client exchanges victim’s auth code set to track the OAuth session at the callback. In some apps,
for an access token and associates this token with attacker’s however, this cookie instead tracks the full user session
app account, as indicated by the fixated OAuth session. of the account linking initiator. As a result, if the pre-
6 As a result, the victim’s connector account is linked to authorization request URL is shared with a victim, an at-
the attacker’s app account. The attacker gains unauthorized tacker can leverage the fixated session to break the integrity
access and can control the connector on the victim’s behalf. of the application’s user session, resulting in Login CSRF
of the app account. Meanwhile, the OAuth flow proceeds
4.1.2. Security Impact. uninterrupted, facilitating connector account takeovers via
Account Takeover. The direct impact is unauthorized ac- COSF, effectively “killing two birds with one stone”.
cess. Notably, as connector authorizations commonly grant
broad scopes for access delegation that resemble user im- 4.2.2. 0-Click Forced Linking of Connector Accounts.
personation, these attacks essentially amount to account The attacks described so far require user interaction. How-
7
ever, if the OAuth session (ID) is guessable and its integrity Authenticated space Unauthenticated space
is not protected (e.g., merely consisting of an 8-digit user
ID, or containing such an ID in a non-signed JSON), forced Start OAuth
linking of connector accounts can occur without any victim user session
interaction. An attacker can forge an OAuth session (ID) /authorize?state=state&redirect_uri=app_backend
and then submit their own auth code at the OAuth callback.
(1) Convert to deeplink
This forces the victim associated with the targeted user ID https://xxx ->
302 redirect
app://xxx
to access the attacker’s connector account at the application.
(4) Match state
to user session user session (deep-link)
4.3. Robust Defenses (5) Proceed with (3) Forward to (2) Return to the
Code Exchange app backend original user-agent
Root Cause. To summarize, cross-user attacks arise be- Figure 11. Robust Defense: Return to and validate at the authenticated space
cause the OAuth client relies on a derived OAuth session, (app’s original origin/UA with user session) maintains session integrity.
instead of the app’s existing user session, to identify the
intended “app account” for account linking. However, it fails implementation that requires a quick fix, or for a cross-
to verify the binding between the two sessions, likely due platform app where a single client_id serves both its web
to the OAuth callback being visited in an unauthenticated and native versions. In such cases, a post-redirect pattern
space, a distinct origin or UA separated from the original au- can be employed: the OAuth callback acts as a proxy that
thenticated space holding the app’s user session. Malicious forwards the auth code and state back to the app’s original
users can exploit this lack of binding to transfer OAuth ses- origin or UA where account linking is initiated.
sions to a victim’s device, enabling session fixation attacks. As an example, the defense in native apps is illustrated
To maintain session integrity during account linking, the in Fig. 11. The callback endpoint converts the request URL it
guiding principle is to ensure that an OAuth flow initiated receives into a deep link and redirects to it, returning control
by one app user is also completed by the same user. to the native app. The app then sends the auth code to its
Practically, this means having the OAuth flow complete at backend and verifies that the logged-in user indeed initiated
an authenticated space, namely, the app’s primary web origin the OAuth session before continuing the code exchange.
or its native app. Robust defenses therefore either directly Defense Comparison. Traditional session fixation in
return to the original origin or UA (D1 and D2), or apply a web security has a well-established defense by rotating
post-redirect pattern that securely bridges the gap between session IDs [10], which is now standard practice in web
origins and UAs (D3). These approaches eliminate insecure applications. In contrast, defending against COSF requires
session passing, ensuring that any passed session is routed verifying the binding between the OAuth session and the
back and validated in the authenticated space.2 existing user session, which is often overlooked.
D1. Web App: Cross-Origin Defense. The application
shall register its OAuth callback endpoint under the same 4.4. Other Valid Countermeasures
origin where its user session resides. Upon OAuth callback,
the app’s backend must verify the OAuth session against In addition to the recommended defenses (D1–D3), we
the user session to ensure that the entire OAuth flow is further outline several additional viable defenses (D4–D6)
both initiated and completed by the same app user, before with their respective limitations.
performing the code exchange. Note that if the “real” OAuth D4. Manually Bridging the Session Gap. Given the
callback processing logic remains on a cross-origin location, heterogeneous publishing channels for agents, their ability to
the app should forward the auth code to the location from handle OAuth callbacks varies. While web and native apps
its backend, rather than exposing a cross-origin callback to can host callbacks directly, agents deployed in constrained
the frontend (UA) as in the vulnerable design. environments, such as bots running on IM platforms, face
D2. Native App: Cross-UA Defense. Native apps should greater challenges. Although callbacks to the IM platform
register their callback endpoint as a native public client [9, itself are feasible (e.g., via HTTPS URLs or deep links), bots
§7] at the connector’s AS. Upon receiving the authorization typically have limited capability to receive such callbacks.
response, the native app should submit the auth code to the This limitation calls for alternative approaches to the post-
OAuth confidential client in the app’s backend. Implementa- redirect pattern. One option is for the OAuth client to display
tions must verify the OAuth session against the user session a PIN code that the user manually enters, similar to mech-
before proceeding with code exchange. anisms used to mitigate phishing attacks in cross-device
D3. Post-redirect Pattern. There are cases where chang- OAuth flows [30, §3.1.3]. The PIN can then be relayed
ing the preregistered callback endpoint on the connector through the channel to app (agent) backend and ultimately
side is impractical: for example, when securing an existing returned to the OAuth client for validation. Alternatively,
connector’s AS may directly employ cross-device flows
2. Note that the defenses D1–D3 still assume the existence of an instead of authorization code grant, as we move toward even
OAuth session. Under the same principle of returning to the authenticated
space, if vendors instead abandon OAuth sessions and rely solely on the
more heterogeneous agent interfaces like headless agents.
app’s user session for user identification at the OAuth client, the session D5. Extra Consent Screen at OAuth Client. An al-
integrity problem reduces to standard OAuth Login CSRF in §2. ternative defense is to require explicit user consent at the
8
pre-authorization request or OAuth callback. This additional OAuth Authorization
consent screen, enforced by the OAuth client, shall display Client Server (AS)
which app user would receive the OAuth token. It comple- Token Vault Connector
ments the original OAuth consent screen at the AS, which OAuth Client
Registration
shows which application would receive the OAuth token.
D6. Re-authentication in the Browser. For native apps, a /authorize?client_id=client &…
straightforward defense is to require users to re-authenticate OAuth Flow … Explicitly
Authorize
the application in the browser, either at the pre-authorization /authorize?client_id=client &…
request or OAuth callback. This would turn the cross-UA OAuth Flow … Auto-Authorize
w/ prior consent
scenario into a same-UA scenario. However, this approach
degrades user experience and may cause confusion. Benign tenant Malicious tenant
Limitations. Figure 12. Cross-tenant Client ID Confusion. A user previously consented
• Defenses that depend on end-user awareness and manual at a benign tenant under a shared client_id of a pre-built connector.
Connector access granted without consent to an attacker-controlled tenant.
decision-making remain vulnerable to phishing attacks.
These include the manual session-transfer method (D4)
USENIX Security '25 · COAT [1] NEW · Cross-tenant COAT
and the extra consent mechanism (D5). (Cross-connector OAuth Account Takeover) in OAuth-as-a-Service
• The defenses D5 and D6 are limited in that the OAuth Integration Platform Connector Tenant Token Vault Connector
client cannot present meaningful user information on the code
code auth
auth Security
consent screen, or enforce re-authentication, when the e.g., auth
boundary
auth
code cod
application’s user session is not tied to a logged-in user Microsoft
Power Automate
e
account but rather an anonymous session. • Attacker: infiltrates via malicious connector • Attacker: infiltrates via malicious tenant ,
• Assumption: integration platform w/ open marketplace can register malicious connectors by design
Other Defenses. Beyond the basic defenses, Ap- • Target: a benign connector in the same platform • Target: any connector in any tenant
pendix A.1 describes tailored post-redirect pattern (D3)
protections for OaaS. Appendix A.2 summarizes common Figure 13. Comparison of (Single-tenant) COAT and Cross-tenant COAT
pitfalls and ineffective defenses, such as PKCE’s [31] in-
ability to mitigate the issue and additional open redirect [32]
risks introduced by improper fixes. Attack. This design introduces the risk of Client ID Con-
fusion. As shown in Fig. 12, consider a user who previously
authorized a benign connector for a trusted agent belonging
5. Cross-tenant Attacks in OAuth-as-a-Service to a benign tenant. Although the resulting access token
is scoped to that tenant, the user’s consent is technically
So far, our analysis focused on scenarios where the
granted to the Token Vault’s shared client ID. Consequently,
application and its OAuth client are maintained by the same
when the same user later interacts with a malicious agent
party. In OaaS, however, the centralized OAuth client (Token
that also relies on the Token Vault, the benign connector
Vault) maintains a third-party relationship with potentially
treats the new authorization request as pertaining to the
untrusted applications (agents) from different tenants. This
already-consented client ID. As a result, access is silently
multi-tenant architecture expands the attack surface and
granted to the malicious agent, contrary to the user’s inten-
enables new cross-tenant confused deputy attacks.
tion to withhold or explicitly consent to the authorization.
In such a setting, while the OAuth connection suffices
Countermeasure: Per-tenant OAuth Client Registration.
for the functional requirement of tracking the tenant and
The root cause of Client ID Confusion is that as mul-
connector, the security requirement further relies on mech-
tiple tenants share the same client ID at a connector, a
anisms native to the OAuth protocol, namely the client ID
malicious tenant can inherit user consent previously granted
and redirection URI, to distinguish them. These identifiers
to a benign tenant. To prevent this issue, OaaS providers
cannot be scoped only at the coarser per-OAuth-client level.
must not supply shared client IDs for tenants in production
environments. Each tenant should instead register its own
5.1. Cross-tenant Client ID Confusion dedicated client ID with the connector’s AS and bring it
to the OaaS (“Bring Your Own client_id”, BYOC). This
Problem Definition. OaaS providers aim to reduce the
ensures that authorization consent is always tied to the
OAuth integration burden for agent developers. Beyond
intended tenant and avoids cross-tenant unauthorized access.
token lifecycle management, many providers offer pre-built
connectors for popular services (e.g., Dropbox, Outlook
Calendar, GitHub) with preconfigured APIs. To support 5.2. Cross-tenant COAT Attack
these tools out of the box, some OaaS providers also
handle OAuth client registration for these connectors, with Problem Setting. Prior work [1] introduces the Cross-
client_id and client_secret baked in. Traditionally, connector OAuth Account Takeover (COAT) attack3 , where
each developer must register their application at the AS to an integration platform, acting as a confused deputy, can
obtain a unique client ID, which identifies the application 3. Originally referred to as “Cross-app OAuth Account Takeover” in [1],
during OAuth flows. In OaaS, however, multiple tenants may where the term “app” denotes SaaS applications integrated within a plat-
share the same built-in client ID assigned to the Token Vault. form, and thus corresponds to the “connector” concept in this paper.
9
leak a victim’s auth code from a benign connector to a 6.1. System Overview of OASIS
malicious one. In the original setting, the attacker relies on
a single tenant—an integration platform serving an open Evaluating COSF vulnerabilities across the industry is
marketplace—to distribute the malicious connector. With non-trivial in two aspects: 1) Identifying in-scope applica-
multi-tenant OaaS, this prerequisite is relaxed. tions. While common integration platforms and agentic AI
Attack. As illustrated in Fig. 13, in OaaS, any developer infrastructures can be readily identified due to their inher-
can create custom agents paired with custom connectors ent reliance on account linking, connector-equipped apps
within their own tenant. Consequently, the presence of a ma- are more difficult to discover, as account linking appears
licious connector no longer depends on an open marketplace, as a secondary feature within broader productivity apps.
but remains applicable even if the targeted benign tenant(s) 2) Assessing vendor susceptibility further requires exten-
are closed ecosystems: an attacker can simply deploy a sive manual testing, since no reliable automated detection
malicious agent that carries a malicious connector in their methods exist. These gaps motivate the development of a
own tenant, and target users of a benign connector carried tool to uncover COSF vulnerabilities.
by a benign tenant, launching Cross-tenant COAT attacks. A major challenge is that COSF vulnerabilities manifest
In an attack flow, the victim establishes account linking in OAuth confidential clients deployed in the cloud, whose
with the malicious connector (as a dummy user of the mali- source code is not publicly available, which precludes direct
cious agent), and is then redirected to authorize the benign static analysis. Our key insight is to shift focus to local code-
connector (as a user of the benign agent). However, the bases instead. Rather than analyzing vulnerability patterns in
resulting auth code is forwarded to the malicious connector cloud-side implementations, we adopt an exclusion-based
in the token request because the OAuth client, based on approach that identifies the absence of certain patterns
the OAuth session, tracks the malicious connector in the in locally-accessible Android app code, which indirectly
authorization context. The attacker can then redeem the signals potential flaws in the corresponding OAuth clients.
stolen auth code at the benign connector (as a user of the To this end, we develop OASIS, a static analyzer capable
benign agent) for connector account takeover. of detecting COSF vulnerabilities in native apps. To our
Countermeasure: Globally-unique redirect_uri. In knowledge, existing OAuth testing tools [7], [8], [33], [34],
the original (single-tenant) COAT vulnerability [1], the [35], [36], [37] neither cover the use case of account linking
OAuth client fails to verify that the connector completing in connector ecosystems nor detect session fixation flaws.
OAuth matches the one that initiated it. In Cross-tenant OASIS follows a two-phase approach, with the workflow
COAT, the OAuth client (Token Vault) further fails to ensure overview shown in Fig. 14. Phase I filters Android appli-
that both connectors belong to the same tenant. To address cations that implement account linking, while Phase II de-
this root cause, the OAuth client shall assign a globally tects COSF vulnerabilities without executing actual OAuth
unique redirect_uri for each connector during client reg- flows or attacks. Another major technical challenge lies in
istration and OAuth flows. This design enables the OAuth accommodating diverse Android app types, such as regular
client to enforce redirect_uri validation not only between native apps written in Java or Kotlin, hybrid apps developed
connectors within the same tenant, but also across tenants. with Ionic or Capacitor, and cross-platform apps built with
The exact implementation of the redirect_uri may vary; React Native. OASIS therefore adopts a lightweight design
for example, using a globally unique connector ID (e.g., h to ensure broad compatibility across such variants.
ttps://oaas.com/callback/), or
combining a tenant ID4 with a tenant-scoped connector ID
(e.g., https://.oaas.com/callback/).
The first phase extracts Android apps that likely support
Comparison: Cross-user vs. Cross-tenant Attacks. Re-
OAuth-based account linking from a large corpus. We utilize
call from §3.4 that an OAuth connection tracks the autho-
AndroZoo [38], a large-scale research dataset of Android
rization context of . The afore-
packages (APKs), and apply a multi-stage filtering pipeline:
mentioned attacks exploit different gaps in this context:
Cross-user attacks break the user binding; Cross-tenant Data Preprocessing. We begin with apps in the Pro-
Client ID Confusion breaks the tenant scoping; and Cross- ductivity category, which, based on our preliminary study,
tenant COAT breaks the connector distinction. exhibit the highest prevalence of account linking. To ensure
relevance, we include only actively maintained apps (up-
dated within the last 6 months) with at least 50K downloads.
6. COSF Vulnerability Detection Each APK is decompiled using Jadx [39] to inspect source
code and resource files. JavaScript bundles are unpacked into
In this section, we propose OASIS (OAuth Session In-
modules, and Hermes bytecode from React Native apps is
tegrity Scanner), a static analyzer that evaluates the preva-
decompiled using hbc-decompiler [40].
lence of COSF vulnerabilities across connector ecosystems.
Heuristic-based Filtering. We then apply a set of static
This section presents its design and implementation.
heuristics to exclude irrelevant apps and isolate OAuth con-
4. Note that enforcing per-tenant redirect_uri alone mitigates Cross- fidential client implementations from the majority use case
tenant COAT, reducing the attack surface to Single-tenant COAT [1]. of public clients:
10
Phase I: Identify Account Linking Apps Phase II: Detect COSF Vulnerabilities
Connector icon–name OAuth Code Exchange OAuth Callback
co-location & API Call Logic Handling Logic
found dropboxapi.com does not exist URL Parsing
Dropbox
Automated Relevant Apps graph.microsoft.com Confidential Client myapp://oauth/callback does not exist
Outlook ... exists ?code=xxx&state=xxx&id_token=xxx
✅ ✅ ❌
Vulnerable to COSF
OneDrive not found Public Client [RFC8252] exists
Irrelevant Apps Secure from COSF
Workflow Virtual Smart e.g.,
Hand-picked Automation Assistant Home Note-taking App
Popular Integration Platforms & Connector-equipped Apps
Figure 14. Overview of OASIS (OAuth Session Integrity Scanner). It follows a two-phase static approach to (I) identify native apps with account linking
support, and (II) detect COSF vulnerabilities.
• Connector Icon–Name Co-location. We detect user 6.3. Phase II: COSF Vulnerability Detection
interfaces (UIs) indicative of account linking by search-
ing resource files for hard-coded connector brand In Phase II, we analyze how each app handles the OAuth
names (e.g., “Dropbox”, “OneDrive”) and correspond- callback. Our key insight is that native apps that robustly
ing logos (based on icon filenames and RGB values of defend against COSF by returning to the original UA (§4.3)
vector graphics). The co-location of references to the would process the OAuth callback within their local code-
connector’s name and logo within the same class or base, making them identifiable through static analysis.
module constitutes a typical account linking interface. This phase extends the exclusion-based approach by
• Rule Out OAuth Public Clients. In Android, most inferring potential vulnerabilities from the absence of OAuth
OAuth use cases involve accessing resources directly callback-handling patterns. Specifically:
from the device as public clients (first-order OAuth). In • If an app contains a class or module that parses both the
contrast, native apps in connector ecosystems operate code and state parameters from the OAuth callback
as confidential clients (second-order OAuth), where URI, but not the id_token, we classify it as Secure.
resources are accessed by the app’s cloud. We therefore • Otherwise, the app is marked as Vulnerable.
exclude apps that directly invoke connectors’ OAuth This heuristic rests on two observations: (1) Mandating the
token endpoints or APIs on-device; the presence of joint presence of code and state helps exclude OAuth-
such hard-coded endpoints indicates a public client unrelated logic that happens to use either parameter name.
implementation. Endpoints for major connectors are (2) Excluding the id_token parameter avoids interference
listed in Table 6 of Appendix B. from OpenID Connect [44], an OAuth-based SSO protocol
• Exclude Local App Interactions. As a supplementary orthogonal to account linking in connector ecosystems.
filtering step, we remove apps that use intents [41] to Implementation. Regardless of the app development
launch locally installed native apps of the connectors framework, handling OAuth callbacks on Android ultimately
(e.g., Dropbox’s file chooser [42]), since such interac- relies on native processing of deep links or app links [45]
tions do not involve OAuth flows. via intents in Java (or Kotlin). In most cases, the intent URI
is also parsed in Java (or Kotlin), as illustrated in Listing 1,
Scope of Connectors. We focus on 3 representative con- before being passed to other frameworks or languages for
nectors: Dropbox, OneDrive, and Outlook Calendar. These further processing.
connectors are well-suited for OASIS’ workflow, because
(1) they avoid the potential interference from OAuth-based 1 @Override
2 protected void onCreate(Bundle savedInstanceState) {
Single Sign-On (SSO) mechanisms (Dropbox is not an SSO 3 super.onCreate(savedInstanceState);
provider, and Microsoft SSO is rarely used [43]); and (2) 4 // Handle OAuth callback
they support silent authorization, enabling stealthy one-click 5 Uri uri = getIntent().getData();
attacks (see §4.1.2). Due to these considerations, Google 6 if (uri != null) {
// Parse callback URI,
products (e.g., Google Drive and Calendar)5 are not in scope. 7
8 // e.g., myapp://oauth/callback?code=12345&state=xyz
Automated and Manual Collection. We augment au- 9 String code = uri.getQueryParameter("code");
tomated filtering with a manually curated application list 10 String state = uri.getQueryParameter("state");
to capture cases missed by static heuristics. Key sources 11 // Further Processing
12 ...
include integration platforms reported in prior research [1], 13 }
along with popular connector-equipped apps such as note- 14 }
taking apps. Applications without Android versions are re-
Listing 1. Example of OAuth callback handling logic in Android
tained separately for evaluation in §7. This process yields a
refined set of apps with verified account linking functional- Therefore, for each app selected in Phase I, we locate
ity, which are subsequently analyzed in Phase II. the callback-parsing logic in the decompiled source code. To
improve precision, we also account for corner cases where
5. Google’s AS does not issue refresh tokens without explicit user con-
URL parsing is implemented in JavaScript, which can occur
sent (according to [44, §11]), which incidentally mitigates one-click COSF in hybrid or cross-platform apps. Specifically, we employ a
attacks on many OAuth clients that require refresh tokens to be returned. regular expression-based approach to identify method names
11
(e.g., getQueryParameter()) and arguments (e.g., "code") obtained through automated filtering and 26 hand-picked.
commonly used in OAuth callback parsing. This simple but We followed §3.3 to analyze their architectural patterns.
effective method maximizes multi-language compatibility. For vendors offering Android mobile apps (27 in total),
Implementation details are summarized in Table 7. we followed OASIS Phase II (§6.3) to automatically detect
COSF vulnerabilities. We further surveyed agentic AI in-
6.4. Discussions frastructures across the industry using keywords such as
“Agent Auth”, “Agent Builder”, and “Agentic Platform”,
Testing Scope. While OASIS is implemented to detect identifying 8 OaaS providers. Cross-tenant threats were
COSF vulnerabilities in Android apps, the methodology triaged via manual inspection of each vendor’s developer
generalizes to iOS and desktop apps. Moreover, a vendor documentation and runtime authorization URLs. Note that
likely exhibits the same vulnerability across all native app although the COVScan tool proposed in [1] can be adapted to
offerings, as COSF is an OAuth client-specific backend flaw. detect Cross-tenant COAT, it was unnecessary, as all tested
Threats to Validity. We acknowledge several limitations vendors (see Table 5) use a shared redirect_uri, causing
of our approach: (1) In Phase I, native apps that fetch early exit in COVScan’s detection flow [1, §7.1].
the account linking page dynamically from the backend Manual Verification. For all 46 vendors, we then manu-
elude the static heuristics. Typical examples include integra- ally conducted proof-of-concept (PoC) exploits to verify the
tion platforms that host hundreds of connectors, where the triaged vulnerabilities, following the attack descriptions in
connector names and icons are unlikely to be hard-coded §4 and §5. In the testbed setup, we isolated the attacker and
in the app’s code. This limitation is partly mitigated by victim using two browser profiles (for web apps) or two
the manual collection, where such platforms are explicitly devices (for native apps). We used separate accounts for
selected. (2) In Phase II, native apps that ensure session test users (of apps and connectors) as well as test tenants,
integrity by re-authenticating end-users in the external UA ensuring no shared state or information exchange between
(defense D6) do not exhibit detectable callback patterns, po- the attacker and victim except for the attack URL.
tentially causing false positives. (3) Native apps that handle Human Effort. In the evaluation, initial testing took
OAuth callbacks locally (thus appearing secure) can still be around 15 minutes per vendor. Producing detailed PoCs and
vulnerable if their backends omit session integrity checks. vulnerability reports for responsible disclosure took about
Such cases cannot be captured by the Phase II analysis, 2 hours per regular vendor and 1–2 days per OaaS vendor.
resulting in false negatives. (4) Native app obfuscation: As
OASIS identifies resource files, method invocations, and web
API calls—rather than control or data flows—using OAuth 7.2. Measurement Study
domain knowledge, it is relatively robust to obfuscation.
We argue that these are inherent limitations of a static Among the 46 vendors surveyed, 42 were found suscep-
analysis approach. Dynamic analysis, however, is impracti- tible to account mislinking.
cal at scale because it requires substantial manual effort to
locate account linking interfaces and trigger OAuth flows 7.2.1. Cross-user Attacks.
for Phase I, which vary widely across app UIs and are often Evaluation Results. Table 3 shows a breakdown of cross-
gated behind subscription paywalls. For Phase II, a dynamic user vulnerabilities: 40 vendors are affected by COSF, of
approach may also suffer from degraded accuracy due to which 3 and 4 are also vulnerable to App Account Login
heterogeneous implementations, while offering limited prac- CSRF and Connector Account Forced Linking, respectively.
tical benefits over manual attack reproduction. For COSF alone, 16 vendors are vulnerable to the case
We acknowledge that Phase I approach is non-exhaustive where a standalone OAuth session ID is introduced, while
and represents a lower bound on real-world account linking the remaining 24 transfer the OAuth session via the state
support. Nevertheless, since account linking is far less preva- parameter. Four apps require advanced techniques for prac-
lent than general OAuth or SSO adoption, our analysis at tical exploitation (labeled as Adv in Table 3), such as by-
this scale still provides a reasonable characterization of the passing short-lived pre-authorization request URL timeouts,
current landscape (see §7). For Phase II, the limited con- or sending attacker-controlled OAuth completion requests
nector choices do not bias vulnerability detection accuracy, after the callback (see Appendix A.2–Ineffective Defenses).
as identified OAuth callback logic is connector-agnostic. RFC Compliance of state Matching. Among the 16
vendors introducing a separate OAuth session ID, only 3 fail
7. Evaluation to bind the state parameter to the OAuth session in cookies
This section presents our measurement and case studies. (which is a form of UA session). This suggests that most
developers strive to meet RFC requirements [28, §4.7.1] of
7.1. Experimental Setup state–UA session binding despite cross-origin or cross-UA
challenges. However, vulnerabilities remain if the OAuth
Initial Triage. The cut-off date for our data collec- session itself is not securely bound to the user session.
tion from AndroZoo [38], [46] was August 2025. Fol- Cross-Origin and Cross-UA Deployments. We identi-
lowing OASIS Phase I (§6.2), we collected 38 connector- fied 27 cross-origin and 38 cross-UA vendors. To character-
equipped apps and integration platforms, including 12 ize vendors’ architectural patterns, we first consider origin
12
Table 3. E VALUATION OF C ROSS - USER ATTACKS IN C ONNECTOR E COSYSTEMS : 40 VENDORS BREAK OAUTH SESSION INTEGRITY.
Architectural Pattern §3.3 OAuth Session Fixation (COSF) §4.1 App Account Connector Account
Category Vendor Type Vendor Name Collection #DLs Cross-Origin Standalone Session in Login CSRF Forced Linking
Cross-UA Detection
/Cross-Site sessionID state §4.2.1 §4.2.2
Profile Connections A Top Social Platform M 500M+ . TP
A Top Note-Taking App M 100M+ . TP
Akiflow I M 50K+ . TP
149 Live Calendar I A 500K+ . TP
Cupla I M 100K+ .Adv TP
FlowSavvy I A 50K+ Secure TN
Calendar Sync Habitify I A 500K+ . TP
Smart Noter I A 1M+ . TP
Upmeet I A 100K+ . TP
Setmore I A 500K+ . TP
Connector-
Harvest M 100K+ . N/A .
Equipped Apps
An Event Management Platform M N/A . N/A
Todoist I A 10M+ Secure TN
OneDrive I A 5B+ . FN
Speechify I A 10M+ . TP
JotterPad I M 5M+ . TP
File Sync / Tanka I M 10K+ . TP
Data Source Import Mylio Photos I A 100K+ .Adv TP
Nozbe Classic I A 100K+ . TP
Cloze I A 100K+ . TP .
A Top Note-Taking App M 10M+ . TP
IFTTT I M 10M+ . TP .
Slack (Workflows) ø M 10M+ .Adv N/A
A Top Productivity Platform M 1M+ . N/A
Workflow Automation n8n § M N/A . N/A
Platforms
A Top AI Orchestration Platform M N/A .Adv N/A
Integrately M N/A . N/A .
Pipedream § M N/A . N/A
Amazon Alexa I M 100M+ . TP
Integration Baidu Xiaodu I M 5M+ . TP .
Platforms
Alibaba AliGenie I M 5M+ . FN .
Le Chat by Mistral AI I M 1M+ . TP
Virtual Assistants
Perplexity AI M 10M+ . N/A
Manus M 1M+ . N/A .
ChatGPT I M 1B+ Secure TN
Claude I M 10M+ Secure TN
Samsung SmartThings I M 1B+ . FN
Smart Homes Xiaomi Home I M 50M+ . TP
Amazon AgentCore § ∀ ∀
M N/A . N/A
Azure API Management M N/A ∀ ∀ Secure N/A
Token Vault / Microsoft Copilot Studio M N/A ∀ ∀ Secure N/A
Agent Auth Solution / Composio § ∀ ∀
Agentic AI M N/A . N/A
AI Agent Builder / ∀ ∀
Infrastructures Arcade § M N/A . N/A
AI Gateway ∀ ∀
(OAuth-as-a-Service) ByteDance Coze M N/A . N/A
Nango § ∀ ∀
M N/A . N/A
ACI.dev § ∀ ∀
M N/A . N/A
Total 46 — — 27/46 38/46 16/46 + 24/46 — 3/46 4/46
/ I: Web/Native app available, and with Account Linking support (Desktop app ø as fallback if Mobile app I is unavailable or unsupported).
: Same-Origin (and Same-Site); : Cross-Origin but Same-Site; : Cross-Site. : Same-UA; : Cross-UA. .: Vulnerable. Adv : Advanced Attack Techniques Required.
Vendor Collection: A = (semi-)Automated, M = Manual. Vendor collected following OASIS Phase I (§6.2).
#DLs: Number of Downloads, statistics from Google Play (or Tencent Yingyongbao for Chinese-only apps).
∀: Support Heterogeneous Publish Channels (within any origin and/or UA, including deployed as bots in Instant Messaging software), beyond the vendor’s official Web app or Native app.
as the primary security boundary, enforced by the same- categories. In these cases, secure OAuth practices should,
origin policy. A cross-origin deployment typically implies in principle, be straightforward, reducing the problem to
that an app’s main functionalities and its OAuth client are implementation flaws within the textbook OAuth model that
viewed, if not deployed, as separate components internally. involves a single origin and UA. Despite this, we speculate
Cross-Site Deployments. We further use the same-site that developers may assume that once authorization context
vs. cross-site distinction to capture whether the callback end- is encoded in the OAuth session, the callback endpoint no
point can access the app’s session cookies. It is interesting to longer needs to consume the user session, resulting in a
investigate why some vendors host callback endpoints cross- false sense of security. This underscores the importance of
site, which prevents them from utilizing the user session. awareness of COSF even in textbook OAuth deployments.
For instance, Habitify hosts its callback endpoint on Google Another possibility is that the OAuth client, despite same-
Cloud Functions while keeping other functionalities under origin, is implemented as a standalone component separate
its own domain. A leading event management platform, al- from those handling user sessions; in such cases, the cross-
though not an OaaS provider, hosts OAuth functionalities on origin countermeasure described in D1 and D3 still apply.
a centralized server for templated event websites deployed Vulnerability Detection with OASIS.
on custom domains. Microsoft acquired Mover.io in 2019 Phase I. The size of initial dataset is 3.6 million non-game
to enhance OneDrive’s file migration feature, yet its OAuth apps from AndroZoo, landing 61,087 apps after filtering by
callback endpoint remained on a non-Microsoft domain. update date and number of downloads. Upon preprocessing,
Same-Origin and Same-UA Deployments. We observed 3,143 APKs of productivity apps were analyzed. As shown
5 vendors that fall into neither cross-origin nor cross-UA in Table 4, 26 Android apps were collected in Phase I. We
13
Table 4. E VALUATION OF OASIS FOR COSF V ULNERABILITY https://attacker.com/authorize issues a crafted redi-
D ETECTION IN M OBILE A PPS rect to https://www.dropbox.com/oauth2/authorize.
This Dropbox authorization URL embeds query parameters
Phase I: Collection (§6.2) Phase II:† Detection (§6.3)
collected from attacker’s interaction with the benign agent’s
Method # Selected # Excluded # TP # FN # TN # FP
Dropbox connector (i.e., with Dropbox’s client_id, the
(semi-)Automated 12 14 shared redirect_uri, and a fresh PKCE code_challenge),
20 3 4 0
Manual 15 N/A
†
while reusing the state value of the victim’s ongoing
Positive (P): vulnerable; Negative (N): secure.
interaction. Eventually, the attacker can redeem the stolen
auth code by continuing their own OAuth flow with Dropbox
then manually verified the presence of account linking and (i.e., the one associated with the code_challenge), thereby
excluded 14 apps: 6 referenced dead code, 3 required paid completing the account takeover (PoC in [15]). Notably, the
subscriptions without free trials, 3 were proprietary apps, attack does not violate CSRF or PKCE protections. Amazon
and 2 offered account linking only in web versions. resolved this vulnerability by assigning globally unique, per-
Phase II. The remaining 12 Android apps were confirmed connector redirect_uris (by appending a UUID suffix to
to support account linking and analyzed along with 15 man- the original URI) and enforcing matching in OAuth flows.
ually selected Android apps in Phase II. Of the 27 vendors,
20 were correctly identified as vulnerable (true positives),
7.3. Case Studies
4 were correctly identified as secure (true negatives), with
3 false negatives and no false positives. False negatives in- Slack (Workflow Builder). Slack enforced a 10-second
clude Samsung SmartThings (absence of server-side session timeout on pre-authorization request URLs, but this does
integrity check despite native callback handling, see §6.4), not mitigate COSF. An attacker can bypass the limit by
OneDrive, and Alibaba AliGenie (interference from other replaying the full OAuth initiation request that generates
secure OAuth features). To further validate the effectiveness the pre-authorization request URL on their own server after
of our approach, we scanned older versions of the 4 true the victim visits the attacker’s website. The attacker then
negative apps that predate their account linking support. immediately redirects the victim to the fresh request URL,
Three were correctly classified as lacking OAuth callbacks, ensuring its validity in an attack.
while Claude was misclassified due to non-standard SSO Harvest. Harvest’s COSF vulnerability affects only its
flow that did not use the id_token parameter. web app, not its mobile app. On mobile, the app acts as a
public client to obtain tokens and forwards them to the app
7.2.2. OAuth-as-a-Service Providers. We evaluated cross- backend for storage and API calls. While this avoids COSF,
user and cross-tenant attack vectors in OaaS providers, with public clients are inherently less secure than confidential
results summarized in Table 5. clients as they lack client authentication. Furthermore, ac-
COSF. Six of the eight providers were vulnerable to cess tokens intended for backend use are exposed on-device,
COSF. Their respective fixes at the time of writing are listed which could have been avoided with a confidential client.
in the table. Notably, one vendor exposed open redirect This illustrates the lack of guidance for implementing secure
issues due to improper COSF defenses (see Appendix A.2). OAuth confidential clients in native apps.
Cross-tenant Client ID Confusion. We examined how Microsoft Copilot Studio. A severe Cross-tenant COAT
vendors support and promote shared client IDs across ten- vulnerability was identified in Microsoft Copilot Studio.
ants. The four vulnerable vendors treat shared client IDs as Each custom agent (called a Copilot) uses the “Bot Frame-
part of their business model, making BYOC optional rather work Token Service” as its Token Vault. Microsoft designed
than a security requirement. For example, Arcade previously this Token Vault to support broader use cases, where agent
stated that “it can be useful” for tenants to configure their developers can not only request tool access (e.g., Dropbox)
own client IDs, but now states: “if you are building a multi- but also authenticate users across different identity providers
user production app, you must obtain your own OAuth app (IdPs, e.g., Microsoft Entra ID), thereby enabling fine-
credentials and add them to Arcade.” [48] after our report. grained access control over who can access each agent.
Cross-tenant COAT. We identified 7 susceptible OaaS Consequently, a Cross-tenant COAT attacker can configure
providers, all of which use a shared redirect_uri across a custom agent with a malicious IdP to access arbitrary
tenants and connectors. As a result, any connector in any well-authenticated agents on the Internet under the victim’s
tenant’s agent relying on these OaaS Token Vaults is vul- identity, gaining access to all their gated resources.
nerable to Cross-tenant COAT. Model Context Protocol (MCP). MCP [49] is an emerg-
As a concrete example, the redirect_uri in Amazon ing standard for AI agent tool-use, in which MCP clients
Bedrock AgentCore https://bedrock-agentcore. .amazonaws.com/identities/oauth2/ca access tokens to MCP servers (APIs) to access protected re-
llback was shared between the malicious tenant’s con- sources. While MCP OAuth [50] is usually considered first-
nector and benign tenant’s connector (e.g., Dropbox). An order OAuth, where the MCP client acts as an OAuth public
attacker can exploit this by tricking a victim into inter- client, COSF attacks can manifest in two MCP scenarios:
acting with an attacker-controlled agent. During account 1) MCP clients of remote MCP hosts. In this case, the
linking, the malicious connector’s authorization endpoint MCP client is an OAuth confidential client. Users maintain
14
Table 5. OAUTH ACCOUNT M ISLINKING V ULNERABILITIES ACROSS OAUTH - AS - A -S ERVICE P ROVIDERS
Cross-user Attacks [§4] Cross-tenant Attacks [§5]
Vendor Name
OAuth Session Fixation (COSF) [§4.1] Countermeasures [§4.3, Appendix A] Client ID Confusion [§5.1] COAT [§5.2]
Amazon Bedrock AgentCore . Fixed Post-redirect Pattern (D3) [3] Secure . Fixed
Secure, except for Post-redirect Pattern (D3) or Extra Consent (D5) [47]
Azure API Management Secure . Fixed
. Microsoft Copilot¶ (Fixed) . Open Redirect×3 (Fixed) [Appendix A.2]
Microsoft Copilot Studio Secure Post-redirect Pattern (D3) or Manual PIN (D4) Secure . Fixed
Composio . Insufficient Fix Shorter Timeout . “recommend” § .†
Arcade . Fixed Post-redirect Pattern (D3) [48] . Fixed (“can”→“must”) . Fixed
ByteDance Coze . Fixed Extra Consent (D5) . Fixing . Fixed
Nango . Secure .†
ACI.dev . . “can” N/A‡
¶ §
A Microsoft first-party tenant of Azure API Management. Requirement level of BYOC (Bring Your Own client_id), the same below.
† ‡
Cross-tenant COAT feasible via pre-built connectors with customizable AS endpoints from attacker’s tenant. No custom(izable) connector support for any tenant.
sessions between their UA and the remote MCP host, and the user, thereby overlooking the threat modeling of session
tokens from MCP servers are linked to the MCP host’s user fixation. We address this gap by examining the motivations
identity, making this a form of second-order OAuth (i.e., and implications of such designs from the perspective of
account linking). We found 2 MCP clients (Manus AI and OAuth architectural patterns, highlighting session fixation
Mistral AI’s Le Chat; see Table 3) susceptible to this issue. as a standalone attack vector across connector ecosystems.
2) MCP servers with downstream API authorization. If Cross-Origin OAuth. D ISTINCT [34] identified security
an MCP server relies on downstream APIs whose credentials issues in dual-window SSO flows, including those that cross
are also fetched via OAuth and associated with the MCP ses- origins. However, the study focuses exclusively on SSO
sion (between MCP client and server), then the downstream and does not cover OAuth authorization scenarios. A key
token retrieval process effectively becomes account linking. distinction also lies in the flow assumptions: SSO may rely
This pattern is standardized in the MCP URL elicitation on cross-origin in-browser communication (InBC) mecha-
proposal [51] by Arcade, a vulnerable agentic AI vendor nisms to return authentication credentials to the application’s
(see Table 5). In addition to reporting vulnerabilities in Ar- primary origin, whereas our COSF attack arises precisely
cade’s OaaS product line [48], we discovered its MCP pro- because such a return is absent. Consequently, cross-origin
posal was also vulnerable and informed Arcade accordingly. InBC mechanisms such as postmessage could serve as an
Arcade subsequently updated its MCP proposal to include alternative to HTTP redirects when enforcing the COSF
a discussion of the session fixation attack vector [52]. defense of post-redirect pattern (D3) to return to the original
authenticated origin.
8. Related Work Brokered OAuth. Like SSO Brokers [54], OaaS with
Token Vaults also extend three-legged OAuth into a four-
actor architecture. However, the two ecosystems exhibit
This section discusses related work from both academia
distinct security issues. The fundamental difference is that
and industry, and highlights how they differ from this work.
brokered SSO designs chain two SSO flows side by side
(App↔Broker and Broker↔AS), whereas only a single
8.1. Related Academic Research OAuth flow is involved in OAuth-connection-based OaaS
designs. In the latter, the Token Vault acts as the sole OAuth
Connector vs. SSO Account Linking. In this work, client; applications retrieve access tokens by 1) authenti-
the account linking concept generally aligns with [1]. It cating to the Token Vault (§3.3), and 2) presenting OAuth
contrasts with SSO account linking [34], [37], [53], where connection IDs (§3.4), which are non-secret identifiers. Con-
a user’s IdP account connects to an application’s existing sequently, each application is exempt from the burden of
account system for SSO. In SSO account linking, account implementing OAuth client logic or managing tokens.
takeovers arise from typical OAuth CSRF vulnerabilities [2,
§10.12], rather than from session fixation issues. 8.2. Related Discussions in Industry
OAuth in Integration Platforms. While (Single-tenant)
COAT attacks in integration platforms [1] are not the focus Despite active discussions on OAuth in the industry,
of this work, they constitute an entry in our attack frame- particularly within standardization bodies such as the IETF
work for connector ecosystems (Table 1), and our Cross- OAuth Working Group and OpenID Foundation, the specific
tenant COAT attack in OaaS builds upon them. Regarding issues uncovered in this work were previously unaddressed.
session integrity, session fixation was not distinguished from OAuth Session Integrity. Session integrity issues are a
CSRF issues in [1]: the authors attributed the potential for classic threat in web security. Prior research has extensively
“one-click” COAT attacks to missing CSRF protection [1, analyzed cookie integrity, leading to multiple updates to the
§4.3], but only analyzed the case of OAuth-initiation CSRF. cookie standard [55], [56]. While attack techniques such as
They did not investigate other causes of CSRF-like behav- cookie tossing are also feasible in OAuth [57], [58], such
iors, where the OAuth callback depends on the OAuth ses- issues depend on ad-hoc OAuth implementations and fall
sion rather than the pre-existing platform session to identify outside the scope of this work.
15
Existing OAuth research on session integrity primarily 9. Conclusion
focuses on (Login) CSRF [2], [59], [60], [54]. Regarding
session fixation, one such attack was previously identified This work presents the first systematic study of archi-
in OAuth 1.0 [61], where the “request token” functioned tectural patterns underlying OAuth-based account linking in
as an OAuth session and could be fixated on a victim’s connector ecosystems. We develop a unified security frame-
device. In OAuth 2.0, the concept of an OAuth session is work for account mislinking threats, including Cross-user
not explicitly defined in the protocol specification, leaving OAuth Session Fixation (COSF), the first session fixation
only the state parameter which may carry authorization attack against implementations of the standard OAuth 2.0
state information. However, as our study reveals, connec- authorization code grant flow. Our semi-automated measure-
tor ecosystems may inevitably introduce standalone OAuth ment uncovers 40 real-world apps, platforms, or infrastruc-
sessions through state parameters or standalone session tures vulnerable to COSF, and further reveals Cross-tenant
IDs, and, more importantly, expose an anti-pattern in which confused deputy flaws in 8 OAuth-as-a-Service providers.
clients solely rely on the fixated OAuth session to identify Our analysis exposes fundamental gaps that warrant
the current authorization context, thereby associating the immediate attention from both the research and standards
access token with an unintended user at the client. communities: (1) Existing OAuth specifications lack nor-
The OAuth community has also discussed remote phish- mative guidance on maintaining session integrity in cross-
ing in cross-device OAuth flows [62, §5.4], [63], as well origin, cross-user-agent, and separate-responsibility scenar-
as session fixation in OpenID for Verifiable Presentations ios. (2) Emerging OAuth-as-a-Service architectures reshape
(OpenID4VP) [64, §14.2]. However, such ecosystems as- traditional trust boundaries. While they offer convenience
sume significantly modified versions of the OAuth protocol, for agentic AI development, their multitenancy may inadver-
handling authorization between a consumption device and tently expose end-users to unauthorized access. This work
an authorization device, or presentations between a verifier represents an initial step toward addressing these gaps; while
and a wallet, with attacks and defenses applicable only the proposed defenses are intuitive and empirically moti-
within those contexts. In contrast, we are the first to analyze vated, formal security proofs remain important future work.
session fixation patterns in the standard authorization code We are working with affected vendors and the IETF to
grant in same-device OAuth flows, which remains suscepti- harden implementations and advance security best practices.
ble to practical real-world attacks.
Furthermore, our COSF attack is stealthier: previous Ethics Considerations
cases required significant social engineering, as victims must
perform user interaction (such as entering a user code) in Considerations for Human Subjects Research. All
cross-device flows [62, §3.3], and should provide explicit experiments were conducted on self-registered test accounts,
consent in OpenID4VP [64, §15.1]. In contrast, COSF without putting humans at risk.
attacks can be triggered simply by tricking victims into Considerations for Vulnerability Disclosure. In accor-
clicking a hyperlink, and attackers can leverage silent autho- dance with responsible disclosure practices, we reported our
rization configured by mainstream ASes to bypass explicit findings to all affected vendors. For each contacted vendor,
user consent, resulting in one-click attacks. Finally, to our we provided a bug report with detailed reproduction steps
knowledge, no prior work has conducted measurement stud- and mitigation strategies, along with a PoC video. As of
ies or proposed vulnerability detection methods for session this writing, we have received acknowledgments from 20
fixation attacks in OAuth(-derived) protocols. vendors (over 15 of which have fixed their issues) and
Decoupled OAuth Architectural Patterns. The “OAuth $35,850 in bug bounties from 11 vendors. We also par-
for Browser-Based Applications” specification [65] de- ticipated in meetings with engineering teams at Microsoft,
scribes the Backend-for-Frontend (BFF) and Token- Arcade, and ByteDance. Arcade published a blog detailing
Mediating Backend (TMB) OAuth architectural patterns. their fix and system re-architecture as a community call-to-
Although account linking in native apps resembles BFF, and action, describing our disclosure as “the first major identity
OaaS providers that return raw access tokens to the apps are vulnerability in agentic AI” [66]. ByteDance issued a formal
comparable to TMB, there are two key differences: letter of appreciation. Amazon [3] and Arcade [48] reused
(1) According to [65], the retrieved tokens are tied to the our root-cause analysis in their updated documentation.
BFF or TMB’s own session, which are generated by BFF We re-tested the vulnerabilities following our disclosure.
or TMB after token retrieval. BFF or TMB-managed tokens Among vendors whose systems were either fixed or not
are not linked to the user’s identity at the browser-based app. vulnerable, 18 vendors adopted COSF defenses D1–D3,
By contrast, the account linking scenario associates tokens 1 adopted D4, 3 adopted D5, and 2 adopted D6. Some
with the app’s user identity, as indicated by the app’s pre- vendors find deploying mitigations challenging, as robust
existing user session. (2) The specification’s security consid- fixes may require cooperation from end-users (to upgrade
erations are scoped to a strong threat model of compromised from deprecated vulnerable native app versions) or OaaS
applications (exploited by malicious JavaScript) in browser- tenant developers (to update their agents and/or connectors).
based apps, whereas the COSF attack in this work assumes We engaged with the IETF OAuth Working Group,
malicious (yet unprivileged) users of a benign application authoring an Internet-Draft [16] to propose updates to the
in web and native apps. published OAuth Security Best Current Practice document
16
(RFC9700 [28]), and subsequently presented and discussed [12] M. Johns, B. Braun, M. Schrank, and J. Posegga, “Reliable protection
the issues during Interim and IETF meetings [67] with the against session fixation attacks,” in Proceedings of the 2011 ACM
Symposium on Applied Computing, 2011, pp. 1531–1537.
Working Group members. The draft highlights (1) the ap- [13] CWE - Common Weakness Enumeration, “CWE-441: Unintended
plication scenario of OAuth Connections/Account Linking, proxy or intermediary (’confused deputy’),” https://cwe.mitre.org/da
and, for both COSF and COAT, (2) the attack descrip- ta/definitions/441.html.
tions and (3) proposed countermeasures, especially cross- [14] n8n-io/n8n, “fix(core): Improve the security on oauth callback end-
points,” https://github.com/n8n-io/n8n/pull/11593.
origin/UA considerations for COSF and cross-tenant con- [15] “Artifacts,” https://mobitec.ie.cuhk.edu.hk/connector-oauth-security.
siderations of globally-unique identifiers for COAT. Our [16] T. Würtele, P. Hosseyni, K. Luo, and A. Fung, “Updates to OAuth
Internet-Draft has been adopted as an OAuth Working- 2.0 Security Best Current Practice,” Internet Engineering Task Force,
Group Draft, reflecting recognition of its practical relevance Internet-Draft draft-ietf-oauth-security-topics-update-01, Mar. 2026,
and impact. work in Progress. https://datatracker.ietf.org/doc/draft-ietf-oauth
-security-topics-update/01/.
[17] T. Lodderstedt, M. McGloin, and P. Hunt, “OAuth 2.0 Threat Model
LLM Usage Considerations and Security Considerations,” RFC 6819, Jan. 2013.
[18] IBM, “What is application integration?” https://www.ibm.com/think/
LLMs were used for editorial purposes in this topics/application-integration.
[19] AWS, “What is application integration? - app integration explained,”
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to ensure accuracy and originality. [20] ——, “What is agentic ai? - agentic ai explained,” https://aws.amaz
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[21] MDN Web Docs, “Same-origin policy - security,” https://developer.
Acknowledgments mozilla.org/en-US/docs/Web/Security/Same-origin_policy.
[22] ——, “eTLD - glossary,” https://developer.mozilla.org/en-US/docs/G
We thank the anonymous reviewers for their help- lossary/eTLD.
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ments and guidance. This work is supported in part by ome/api-keys.
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Figure 15. COSF Defense in OAuth-as-a-Service
18
wards the original authorization data (code and state) as from Microsoft (see Table 5). While mitigating COSF via
a proxy, the OAuth callback may alternatively consume the the post-redirect pattern defense, its Token Vault (“Creden-
authorization data and emit a fresh nonce for subsequent ses- tial Manager” [4]) exposed open redirect issues in Microsoft
sion integrity validation. Such design is common in OaaS, first-party applications that rely on it. In Microsoft Copilot,
as it prevents applications from directly handling raw OAuth the Token Vault did not validate post-redirect URLs, allow-
credentials, consistent with the decoupled business model. ing an attacker to tamper with them to leak authorization
Two vendors that adopted this defense in their vulnerability credentials to any attacker-controlled domain. In Microsoft
fixes are documented in [3], [48]. Power Apps and Azure Logic Apps, the Token Vault validated
post-redirect URLs only up to the root domain, leaving
Takeaway. Even in OAuth-as-a-Service architectures that subdomains and path components as wildcards. As a result,
aim to fully decouple OAuth client logic from the ap- an attacker could specify the post-redirect URL to locations
plication, the application itself must still assume certain capable of exfiltrating authorization credentials, for exam-
OAuth responsibilities for security purposes. ple, pages with Cross-site Scripting (XSS) or postMessage
vulnerabilities [33], [34] on Microsoft-owned domains.
A.2. Common Pitfalls and Ineffective Defenses To prevent this, the post-redirect URL should be pre-
configured at the OAuth client and validated using exact
The following discusses several general caveats: bad string matching in OAuth flows, without any wildcards. Ide-
practices that should be avoided and invalid mechanisms ally, the post-redirect URL should not accept any frontend-
that offer little value as a defense. supplied values at all.
Common Pitfalls.
1) Do not set the app’s full user session during the account Insight. A common source of open redirects in textbook
linking process. Doing so enables Login CSRF attacks OAuth is the redirection from AS to the OAuth client [28,
of app accounts (see §4.2.1). §4.11]: the auth code can be leaked if the OAuth callback
2) Always generate OAuth session IDs dynamically with location is controlled by an attacker. Here, the additional
sufficient entropy. Predictable identifiers invite brute- post-redirect from the OAuth client to the application can
force attacks (see §4.2.2). unintentionally reintroduce open redirect vulnerabilities if
3) Avoid treating the native app entirely as a public client the COSF defense is not implemented securely.
per RFC8252 [9], i.e., obtaining an access token on-
device and then sending it to the app backend for Appendix B.
account linking. This approach is susceptible to access Implementation Details of OASIS
token exposure (see the Harvest case study in §7.3).
Ineffective Defenses. The details of OASIS for identifying OAuth public client
1) Proof Key for Code Exchange (PKCE) [31] does not (in Phase I) and OAuth callback handling logic (in Phase II)
resolve the problem. PKCE only preserves the binding are shown in Table 6 and Table 7, respectively.
between the authorization request and token request,
but not between the initiation of OAuth (generating the Table 6. T OKEN AND API E NDPOINTS OF P OPULAR C ONNECTORS ,
authorization request) and the authorization request. In REFERENCED BY OASIS P HASE I TO EXCLUDE OAUTH PUBLIC CLIENTS .
fact, in a COSF attack, both the authorization request Connector OAuth Token Endpoints API Endpoints (Prefix)
and token request are completed in a single OAuth flow. api.{dropbox,dropboxapi}.com
Dropbox {api,content}.dropboxapi.com
2) Short-lived (pre-)authorization request URL is ineffec- /oauth2/token
graph.microsoft.com/v1.0
tive as a sole defense (see the Slack case study in §7.3). /{me/drive,drives/*}
login.microsoftonline.com
3) Additional “completion” steps after the OAuth callback OneDrive
/common/oauth2/v2.0/token graph.microsoft.com/v1.0
/{groups,sites,users}/*/drive
are ineffective if they rely on attacker-controlled data.
Outlook login.microsoftonline.com graph.microsoft.com/v1.0
For example, sending an OAuth completion request Calendar /common/oauth2/v2.0/token /me/{calendar*,events,findMeetingTimes}
with simply a success message (e.g., https://app.
com/oauth/complete?success=true) or reusing the
OAuth session ID (e.g., https://app.com/oauth/co Table 7. S CREENING LOGIC USED BY OASIS P HASE II. A N A NDROID
APP IS CONSIDERED TO HANDLE OAUTH CALLBACKS IF IT SATISFIES
mplete?sessionID=foobar) are insufficient. As such ANY OF THE FOLLOWING RULES . E ACH RULE SPECIFIES PATTERNS
information is known to the attacker, the completion THAT MUST AND MUST NOT BE PRESENT, EVALUATED WITHIN THE
request can be forged and therefore cannot defend SAME CLASS OR MODULE .
against COSF. Category Detection Rule
Caveat: Open Redirect. The post-redirect pattern (D3) Uri AND .getQueryParameter("code") AND .getQueryParameter("state")
AND NOT .getQueryParameter("id_token")
is a robust defense against COSF. However, if an attacker Java
(regular Native apps) JSONObject AND .getString("code") AND .getString("state")
can control the target location of the post-redirect, this AND NOT .getString("id_token")
would inadvertently create an auth code exfiltration channel, (URL.searchParams OR URLSearchParams)
JavaScript / TypeScript AND .code AND .state AND NOT .id_token
resulting in open redirect [32] flaws. (Hybrid apps or
(URL.searchParams OR URLSearchParams)
Cross-platform apps)
In our study, we discovered three real-world vulnerabil- AND .get("code") AND .get("state") AND NOT .get("id_token")
ity instances in Azure API Management, an OaaS provider
19
Appendix C. 2) Mitigations. The defenses presented are intuitive but
Meta-Review not formally analyzed or proven to be robust. No
systematic evaluation of mitigation effectiveness is pro-
The following meta-review was prepared by the program vided, and it is unclear whether some attack vectors
committee for the 2026 IEEE Symposium on Security and may remain even after proposed fixes are applied.
Privacy (S&P) as part of the review process as detailed in
the call for papers.
C.1. Summary
The paper examines the security of OAuth-based account
linking in connector ecosystems and OAuth-as-a-Service
(OaaS) infrastructures. It identifies new attack vectors in-
cluding Cross-user OAuth Session Fixation (COSF) and
cross-tenant confused deputy attacks, presents OASIS (a
static analysis framework for detecting these vulnerabilities
in Android apps), and evaluates the prevalence of the attacks
across popular vendors, with responsible disclosure leading
to vendor acknowledgments and fixes.
C.2. Scientific Contributions
• Creates a New Tool to Enable Future Science.
• Identifies an Impactful Vulnerability.
• Provides a Valuable Step Forward in an Established
Field.
C.3. Reasons for Acceptance
1) Identifies an Impactful Vulnerability. The paper iden-
tifies a new attack surface for OAuth 2.0 in account
linking scenarios that have not been previously studied.
The findings involve major vendors including Slack
and Amazon Bedrock AgentCore, with 40 vendors
confirmed susceptible to COSF attacks and 8 OaaS
providers susceptible to cross-tenant attacks. Most ven-
dors acknowledged and partially deployed mitigations
following responsible disclosure.
2) Creates a New Tool to Enable Future Science. The
paper presents OASIS, a static analysis framework
that enables the detection of account linking flaws
and COSF vulnerabilities in mobile apps. This tool
represents a first step toward automated analysis of
OAuth-based account linking flows.
3) Provides a Valuable Step Forward in an Established
Field. The paper advances understanding of OAuth
security by analyzing the connector ecosystem/OaaS
attack surface, combining empirical analysis, case stud-
ies, and recommended mitigations.
C.4. Noteworthy Concerns
1) Limitations of the OASIS tool. The analysis relies
on static heuristics, works only on Android apps, and
detects only COSF vulnerabilities. The effectiveness
of the first phase of OASIS is questionable. The tool
requires substantial manual effort to confirm findings.
20