detecting-oauth-token-theft▌
mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026
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Detects and responds to OAuth token theft and replay attacks in cloud environments, focusing on Microsoft Entra ID (Azure AD) token protection, conditional access policies, and sign-in anomaly detection. Covers access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, and pass-the-cookie attacks. Activates for requests involving OAuth token theft detection, token replay prevention, Azure AD conditional access token protection, or cloud identity attack investigation.
| name | detecting-oauth-token-theft |
| description | 'Detects and responds to OAuth token theft and replay attacks in cloud environments, focusing on Microsoft Entra ID (Azure AD) token protection, conditional access policies, and sign-in anomaly detection. Covers access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, and pass-the-cookie attacks. Activates for requests involving OAuth token theft detection, token replay prevention, Azure AD conditional access token protection, or cloud identity attack investigation. ' |
| domain | cybersecurity |
| subdomain | cloud-security |
| tags | - oauth - token-theft - azure-ad - entra-id - conditional-access - token-replay - identity-security - PRT |
| version | 1.0.0 |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | - PR.IR-01 - ID.AM-08 - GV.SC-06 - DE.CM-01 |
Detecting OAuth Token Theft
When to Use
- Investigating alerts for impossible travel or anomalous token usage in Microsoft Entra ID
- Responding to a suspected session hijacking or pass-the-cookie attack
- Configuring proactive defenses against OAuth token theft in an Azure/M365 environment
- Detecting OAuth device code phishing campaigns that bypass MFA
- Analyzing sign-in logs for token replay indicators
- Implementing Token Protection conditional access policies to bind tokens to devices
Do not use for on-premises Kerberos ticket attacks (pass-the-ticket, golden ticket); use Active Directory-specific investigation techniques for those scenarios.
Prerequisites
- Microsoft Entra ID P2 license (required for Identity Protection risk detections and conditional access)
- Global Administrator or Security Administrator role in the Entra admin center
- Microsoft Defender for Cloud Apps (MDCA) license for session anomaly detection
- Access to Entra ID Sign-in Logs and Audit Logs (requires Diagnostic Settings configured to Log Analytics or Sentinel)
- Familiarity with OAuth 2.0 authorization flows (authorization code, device code, client credentials)
- Microsoft Sentinel or equivalent SIEM ingesting Entra ID sign-in and audit logs
Workflow
Step 1: Understand the Token Theft Attack Surface
Identify which token types are at risk and how they are stolen:
Token Type | Lifetime | Theft Vector | Impact
----------------------|-------------|----------------------------------|------------------
Access Token | 60-90 min | Memory dump, proxy interception | API access for token lifetime
Refresh Token | Up to 90 days| Browser cookie theft, malware | Persistent access, new access tokens
Primary Refresh Token | Session-based| Mimikatz, AADInternals, malware | Full SSO to all M365/Azure apps
Session Cookie | Varies | XSS, browser exploit, AitM proxy | Full session hijacking
Device Code Token | 15 min auth | Phishing (device code flow abuse)| Attacker gets refresh token via social engineering
Common attack techniques:
- AitM Phishing (Adversary-in-the-Middle): Attacker proxies the legitimate login page via tools like Evilginx2, capturing session cookies and tokens after the user completes MFA
- Device Code Phishing: Attacker generates a device code, sends it to the victim via email/Teams, victim authenticates, attacker receives the token
- PRT Extraction: Attacker with local admin on a device extracts the Primary Refresh Token using Mimikatz (
sekurlsa::cloudap) or AADInternals - Browser Cookie Theft: Malware or infostealer exfiltrates browser cookies containing session tokens
Step 2: Configure Entra ID Sign-in Risk Detection
Enable Identity Protection to flag anomalous token usage:
Entra Admin Center > Protection > Identity Protection > Risk Detections
Key risk detections for token theft:
- Anomalous Token : Token has unusual characteristics (claim anomalies)
- Token Issuer Anomaly : Token issued by an unusual token issuer
- Unfamiliar Sign-in : Sign-in from a location not seen before for the user
- Impossible Travel : Sign-ins from geographically distant locations in impossible time
- Malicious IP Address : Sign-in from a known malicious IP
- Suspicious Browser : Sign-in from a suspicious or attacker-controlled browser
Configure risk-based conditional access:
Entra Admin Center > Protection > Conditional Access > New Policy
Policy Name: "Block High-Risk Sign-ins - Token Theft Protection"
Assignments:
Users: All users (exclude break-glass accounts)
Cloud Apps: All cloud apps
Conditions:
Sign-in Risk: High
Grant:
Block access
Policy Name: "Require MFA for Medium-Risk Sign-ins"
Assignments:
Users: All users
Cloud Apps: All cloud apps
Conditions:
Sign-in Risk: Medium
Grant:
Require multifactor authentication
Require password change
Step 3: Enable Token Protection (Preview)
Configure Token Protection to bind sign-in session tokens to the device:
Entra Admin Center > Protection > Conditional Access > New Policy
Policy Name: "Enforce Token Protection for Desktop Sessions"
Assignments:
Users: All users (start with a pilot group)
Cloud Apps: Office 365 Exchange Online, Office 365 SharePoint Online
Conditions:
Device Platforms: Windows
Session:
Require token protection for sign-in sessions (Preview): Enabled
Grant:
Require device to be marked as compliant
OR Require Hybrid Azure AD joined device
Token Protection ensures that access tokens are cryptographically bound to the device's Trusted Platform Module (TPM). If an attacker steals a token and replays it from a different device, the token is rejected because the proof-of-possession key does not match.
Step 4: Detect Token Replay in Sign-in Logs
Query Entra sign-in logs for indicators of token theft:
// KQL query for Microsoft Sentinel or Log Analytics
// Detect sign-ins where the token was issued in one location and used in another
SigninLogs
| where TimeGenerated > ago(7d)
| where RiskDetail contains "token" or RiskEventTypes_V2 has "anomalousToken"
| project TimeGenerated, UserPrincipalName, IPAddress, Location,
RiskDetail, RiskLevelDuringSignIn, AppDisplayName,
DeviceDetail, ClientAppUsed, TokenIssuerType
| sort by TimeGenerated desc
// Detect impossible travel with token reuse
SigninLogs
| where TimeGenerated > ago(7d)
| where ResultType == 0 // Successful sign-ins only
| summarize Locations=make_set(Location), IPs=make_set(IPAddress),
Count=count() by UserPrincipalName, bin(TimeGenerated, 1h)
| where array_length(Locations) > 1
| sort by TimeGenerated desc
// Detect device code flow abuse (often used in phishing)
SigninLogs
| where TimeGenerated > ago(7d)
| where AuthenticationProtocol == "deviceCode"
| project TimeGenerated, UserPrincipalName, IPAddress, Location,
AppDisplayName, DeviceDetail, ResultType
| sort by TimeGenerated desc
// Detect token replay: same token used from multiple IPs
AADNonInteractiveUserSignInLogs
| where TimeGenerated > ago(7d)
| where ResultType == 0
| summarize IPs=make_set(IPAddress), IPCount=dcount(IPAddress)
by UserPrincipalName, CorrelationId
| where IPCount > 1
| sort by IPCount desc
Step 5: Investigate and Respond to Token Theft
When a token theft event is detected, follow this response procedure:
# Step 5a: Revoke all refresh tokens for the compromised user
# Microsoft Graph PowerShell
Connect-MgGraph -Scopes "User.ReadWrite.All"
Revoke-MgUserSignInSession -UserId "[email protected]"
# Step 5b: Force password reset
Update-MgUser -UserId "[email protected]" -PasswordProfile @{
ForceChangePasswordNextSignIn = $true
}
# Step 5c: Review and revoke OAuth app consent grants
# Check for malicious app consent (common post-compromise persistence)
Get-MgUserOauth2PermissionGrant -UserId "[email protected]" |
Select-Object ClientId, ConsentType, Scope
# Remove suspicious OAuth grants
Remove-MgOauth2PermissionGrant -OAuth2PermissionGrantId "<grant-id>"
# Step 5d: Review enterprise app registrations for rogue apps
Get-MgServicePrincipal -Filter "displayName eq 'Suspicious App'" |
Select-Object AppId, DisplayName, SignInAudience
# Step 5e: Check for mail forwarding rules (common post-compromise action)
Get-MgUserMailFolderRule -UserId "[email protected]" -MailFolderId "Inbox" |
Where-Object { $_.Actions.ForwardTo -ne $null -or $_.Actions.RedirectTo -ne $null }
Step 6: Implement Continuous Access Evaluation (CAE)
Enable CAE to revoke tokens in near-real-time when conditions change:
Entra Admin Center > Protection > Conditional Access > Continuous Access Evaluation
Settings:
Strictly enforce location policies: Enabled
CAE ensures that when you revoke a user's session or change their
risk level, the enforcement happens within minutes rather than waiting
for the access token to naturally expire (60-90 minutes).
Critical events that trigger immediate token revocation with CAE:
- User account disabled or deleted
- Password changed or reset
- MFA enabled for the user
- Admin explicitly revokes refresh tokens
- Azure AD Identity Protection detects elevated user risk
- Network location change violates conditional access policy
Step 7: Configure Defender for Cloud Apps Session Policies
Set up real-time session monitoring to detect and block suspicious token usage:
Microsoft Defender for Cloud Apps > Policies > Session Policies
Policy: "Block download from unmanaged device with stolen token"
Session Control Type: Monitor and block activities
Activity Source: App = Office 365, SharePoint Online
Activity Filter: Device tag does not equal "Compliant"
Activity Type: Download
Action: Block
Policy: "Alert on mass file download (exfiltration via stolen token)"
Session Control Type: Monitor only
Activity Source: App = Office 365
Activity Filter: Repeated activity > 10 downloads in 5 minutes
Action: Alert administrators
Key Concepts
| Term | Definition |
|---|---|
| Primary Refresh Token (PRT) | A long-lived token issued to a registered device that provides SSO to all Azure AD-integrated applications, cryptographically bound to the device's TPM |
| Token Protection | Entra ID conditional access feature that binds sign-in session tokens to the device, preventing replay from other devices |
| Continuous Access Evaluation (CAE) | Protocol that enables near-real-time enforcement of security policies by allowing resource providers to subscribe to Entra ID critical events |
| AitM (Adversary-in-the-Middle) | Phishing technique where an attacker proxies the legitimate authentication flow to capture session cookies after the victim completes MFA |
| Device Code Flow | OAuth 2.0 authorization grant for input-constrained devices; abused by attackers who send device codes to victims via phishing |
| Proof of Possession (PoP) | Cryptographic mechanism where a token includes a claim tied to a device key, ensuring the token can only be used by the device that obtained it |
| Refresh Token | Long-lived OAuth token (up to 90 days) used to obtain new access tokens without re-authentication; primary target for persistent access |
Verification
- Identity Protection risk detections are enabled and generating alerts for anomalous token activity
- Conditional access policies block high-risk sign-ins and require MFA for medium-risk
- Token Protection policy is applied to pilot group and confirmed working (test from unregistered device fails)
- KQL queries in Sentinel return results when tested against synthetic token anomaly events
- Continuous Access Evaluation is enabled and verified (revoke session, confirm access blocked within minutes)
- Defender for Cloud Apps session policies are active and monitoring download activity
- Device code flow is restricted via conditional access (block or require compliant device)
- Incident response runbook includes token revocation, password reset, and OAuth consent review steps
- Mail forwarding rules and OAuth app grants are audited for compromised accounts
How to use detecting-oauth-token-theft on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add detecting-oauth-token-theft
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches detecting-oauth-token-theft from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate detecting-oauth-token-theft. Access the skill through slash commands (e.g., /detecting-oauth-token-theft) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★56 reviews- ★★★★★Pratham Ware· Dec 28, 2024
Solid pick for teams standardizing on skills: detecting-oauth-token-theft is focused, and the summary matches what you get after install.
- ★★★★★Kiara Mensah· Dec 28, 2024
We added detecting-oauth-token-theft from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kabir Martinez· Dec 24, 2024
We added detecting-oauth-token-theft from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chaitanya Patil· Dec 20, 2024
Useful defaults in detecting-oauth-token-theft — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Jin Verma· Dec 12, 2024
detecting-oauth-token-theft fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Jin Mehta· Dec 12, 2024
detecting-oauth-token-theft reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kiara Perez· Nov 19, 2024
detecting-oauth-token-theft reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kaira Jain· Nov 15, 2024
detecting-oauth-token-theft reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Jin Torres· Nov 15, 2024
Solid pick for teams standardizing on skills: detecting-oauth-token-theft is focused, and the summary matches what you get after install.
- ★★★★★Piyush G· Nov 11, 2024
detecting-oauth-token-theft is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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