The SentinelOne Annual Threat Report - A Defenders Guide from the FrontlinesThe SentinelOne Annual Threat ReportGet the Report
Experiencing a Breach?Blog
Get StartedContact Us
SentinelOne
  • Platform
    Platform Overview
    • Singularity Platform
      Welcome to Integrated Enterprise Security
    • AI for Security
      Leading the Way in AI-Powered Security Solutions
    • Securing AI
      Accelerate AI Adoption with Secure AI Tools, Apps, and Agents.
    • How It Works
      The Singularity XDR Difference
    • Singularity Marketplace
      One-Click Integrations to Unlock the Power of XDR
    • Pricing & Packaging
      Comparisons and Guidance at a Glance
    Data & AI
    • Purple AI
      Accelerate SecOps with Generative AI
    • Singularity Hyperautomation
      Easily Automate Security Processes
    • AI-SIEM
      The AI SIEM for the Autonomous SOC
    • AI Data Pipelines
      Security Data Pipeline for AI SIEM and Data Optimization
    • Singularity Data Lake
      AI-Powered, Unified Data Lake
    • Singularity Data Lake for Log Analytics
      Seamlessly Ingest Data from On-Prem, Cloud or Hybrid Environments
    Endpoint Security
    • Singularity Endpoint
      Autonomous Prevention, Detection, and Response
    • Singularity XDR
      Native & Open Protection, Detection, and Response
    • Singularity RemoteOps Forensics
      Orchestrate Forensics at Scale
    • Singularity Threat Intelligence
      Comprehensive Adversary Intelligence
    • Singularity Vulnerability Management
      Application & OS Vulnerability Management
    • Singularity Identity
      Identity Threat Detection and Response
    Cloud Security
    • Singularity Cloud Security
      Block Attacks with an AI-Powered CNAPP
    • Singularity Cloud Native Security
      Secure Cloud and Development Resources
    • Singularity Cloud Workload Security
      Real-Time Cloud Workload Protection Platform
    • Singularity Cloud Data Security
      AI-Powered Threat Detection for Cloud Storage
    • Singularity Cloud Security Posture Management
      Detect and Remediate Cloud Misconfigurations
    Securing AI
    • Prompt Security
      Secure AI Tools Across Your Enterprise
  • Why SentinelOne?
    Why SentinelOne?
    • Why SentinelOne?
      Cybersecurity Built for What’s Next
    • Our Customers
      Trusted by the World’s Leading Enterprises
    • Industry Recognition
      Tested and Proven by the Experts
    • About Us
      The Industry Leader in Autonomous Cybersecurity
    Compare SentinelOne
    • Arctic Wolf
    • Broadcom
    • CrowdStrike
    • Cybereason
    • Microsoft
    • Palo Alto Networks
    • Sophos
    • Splunk
    • Trellix
    • Trend Micro
    • Wiz
    Verticals
    • Energy
    • Federal Government
    • Finance
    • Healthcare
    • Higher Education
    • K-12 Education
    • Manufacturing
    • Retail
    • State and Local Government
  • Services
    Managed Services
    • Managed Services Overview
      Wayfinder Threat Detection & Response
    • Threat Hunting
      World-Class Expertise and Threat Intelligence
    • Managed Detection & Response
      24/7/365 Expert MDR Across Your Entire Environment
    • Incident Readiness & Response
      DFIR, Breach Readiness, & Compromise Assessments
    Support, Deployment, & Health
    • Technical Account Management
      Customer Success with Personalized Service
    • SentinelOne GO
      Guided Onboarding & Deployment Advisory
    • SentinelOne University
      Live and On-Demand Training
    • Services Overview
      Comprehensive Solutions for Seamless Security Operations
    • SentinelOne Community
      Community Login
  • Partners
    Our Network
    • MSSP Partners
      Succeed Faster with SentinelOne
    • Singularity Marketplace
      Extend the Power of S1 Technology
    • Cyber Risk Partners
      Enlist Pro Response and Advisory Teams
    • Technology Alliances
      Integrated, Enterprise-Scale Solutions
    • SentinelOne for AWS
      Hosted in AWS Regions Around the World
    • Channel Partners
      Deliver the Right Solutions, Together
    • SentinelOne for Google Cloud
      Unified, Autonomous Security Giving Defenders the Advantage at Global Scale
    • Partner Locator
      Your Go-to Source for Our Top Partners in Your Region
    Partner Portal→
  • Resources
    Resource Center
    • Case Studies
    • Data Sheets
    • eBooks
    • Reports
    • Videos
    • Webinars
    • Whitepapers
    • Events
    View All Resources→
    Blog
    • Feature Spotlight
    • For CISO/CIO
    • From the Front Lines
    • Identity
    • Cloud
    • macOS
    • SentinelOne Blog
    Blog→
    Tech Resources
    • SentinelLABS
    • Ransomware Anthology
    • Cybersecurity 101
  • About
    About SentinelOne
    • About SentinelOne
      The Industry Leader in Cybersecurity
    • Investor Relations
      Financial Information & Events
    • SentinelLABS
      Threat Research for the Modern Threat Hunter
    • Careers
      The Latest Job Opportunities
    • Press & News
      Company Announcements
    • Cybersecurity Blog
      The Latest Cybersecurity Threats, News, & More
    • FAQ
      Get Answers to Our Most Frequently Asked Questions
    • DataSet
      The Live Data Platform
    • S Foundation
      Securing a Safer Future for All
    • S Ventures
      Investing in the Next Generation of Security, Data and AI
  • Pricing
Get StartedContact Us
CVE Vulnerability Database
Vulnerability Database/CVE-2023-49060

CVE-2023-49060: Firefox iOS Information Disclosure Flaw

CVE-2023-49060 is an information disclosure vulnerability in Mozilla Firefox for iOS that allows attackers to access internal pages or data via ReaderMode. This article covers technical details, affected versions, and steps.

Published: January 28, 2026

CVE-2023-49060 Overview

CVE-2023-49060 is a critical information disclosure vulnerability affecting Mozilla Firefox for iOS that enables attackers to exfiltrate security keys from the browser's ReaderMode feature via the referrerpolicy attribute. This vulnerability allows unauthorized access to internal pages and sensitive data through improper handling of referrer policy directives within the ReaderMode implementation.

Critical Impact

Attackers can extract security keys from ReaderMode to gain unauthorized access to internal browser pages and sensitive user data without requiring any user interaction or authentication.

Affected Products

  • Mozilla Firefox for iOS versions prior to 120
  • Firefox ReaderMode component on iPhone OS
  • All users of Firefox for iOS not updated to version 120 or later

Discovery Timeline

  • 2023-11-21 - CVE-2023-49060 published to NVD
  • 2024-11-21 - Last updated in NVD database

Technical Details for CVE-2023-49060

Vulnerability Analysis

This vulnerability resides in the ReaderMode functionality of Firefox for iOS, specifically in how the browser handles the referrerpolicy HTML attribute. ReaderMode is designed to provide a distraction-free reading experience by stripping away unnecessary page elements, but the implementation contained a flaw that exposed internal security mechanisms.

The core issue stems from improper information exposure where security keys used internally by the ReaderMode feature could be leaked through referrer headers when the referrerpolicy attribute was manipulated by a malicious actor. This allows an attacker-controlled page to capture these security keys and subsequently use them to access privileged internal browser pages or sensitive data that should be protected.

The attack can be executed remotely over the network, requires no special privileges, and does not necessitate any user interaction—making it particularly dangerous for unsuspecting users browsing attacker-controlled websites.

Root Cause

The root cause of this vulnerability is improper information exposure through the referrer policy mechanism. The ReaderMode implementation failed to properly sanitize or restrict the transmission of security keys when processing pages with attacker-controlled referrerpolicy attributes. This allowed sensitive internal tokens to be included in referrer headers and subsequently captured by external servers.

The vulnerability falls under the category of information leakage where browser-internal security credentials were inadvertently exposed to potentially malicious websites through standard HTTP referrer mechanisms.

Attack Vector

The attack vector for CVE-2023-49060 is network-based and involves the following exploitation flow:

An attacker crafts a malicious webpage containing specific referrerpolicy attribute configurations designed to trigger the security key leakage. When a Firefox for iOS user visits this page and engages the ReaderMode feature, the browser inadvertently includes internal security keys in HTTP referrer headers sent to attacker-controlled endpoints.

Once the attacker captures these security keys, they can replay them to access internal Firefox pages or data stores that rely on these keys for authorization. The vulnerability requires no authentication and can be exploited without any user interaction beyond normal browsing activity.

For technical details on the exploitation mechanism, refer to the Mozilla Bug Report #1861405 and the Mozilla Security Advisory MFSA-2023-51.

Detection Methods for CVE-2023-49060

Indicators of Compromise

  • Unusual referrer headers originating from Firefox for iOS ReaderMode sessions containing unexpected token patterns
  • Network traffic to unknown external domains during ReaderMode activation
  • Evidence of internal page access from unauthorized sessions or contexts
  • Abnormal HTTP referrer values in server logs when users access ReaderMode content

Detection Strategies

  • Monitor network traffic for anomalous referrer header patterns when ReaderMode is active on iOS devices
  • Implement network-based detection for connections to known malicious domains during browser sessions
  • Review web server logs for unusual referrer strings that may indicate attempted key exfiltration
  • Deploy endpoint detection rules to identify Firefox for iOS versions prior to 120 in the environment

Monitoring Recommendations

  • Maintain an inventory of Firefox for iOS versions across mobile device fleets using MDM solutions
  • Configure network monitoring to alert on suspicious outbound traffic patterns from iOS devices
  • Implement web filtering to block access to known exploit delivery sites
  • Enable enhanced logging for mobile browser network activity in enterprise environments

How to Mitigate CVE-2023-49060

Immediate Actions Required

  • Update Firefox for iOS to version 120 or later immediately to remediate the vulnerability
  • Review mobile device management policies to ensure timely browser updates are enforced
  • Consider temporarily disabling ReaderMode on unpatched devices if immediate updates are not possible
  • Audit recent network traffic from iOS devices for potential exploitation indicators

Patch Information

Mozilla has addressed this vulnerability in Firefox for iOS version 120. Users should update their browser through the Apple App Store to receive the security fix. The official security advisory is available at Mozilla Security Advisory MFSA-2023-51.

Organizations using mobile device management (MDM) solutions should push the Firefox for iOS update to all managed devices and verify installation completion.

Workarounds

  • Avoid using ReaderMode on untrusted websites until the browser is updated
  • Use alternative browsers on iOS devices until Firefox can be patched
  • Implement network-level controls to restrict access to potentially malicious sites
  • Educate users about the risks of browsing untrusted content with vulnerable browser versions
bash
# Verify Firefox for iOS version via MDM
# Ensure version 120 or later is deployed across all managed iOS devices
# Example: Check app inventory for Firefox versions below 120
mdm-query --app "Firefox" --platform ios --version-below "120"

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

  • Vulnerability Details
  • TypeInformation Disclosure

  • Vendor/TechMozilla Firefox

  • SeverityCRITICAL

  • CVSS Score9.8

  • EPSS Probability0.46%

  • Known ExploitedNo
  • CVSS Vector
  • CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
  • Impact Assessment
  • ConfidentialityLow
  • IntegrityNone
  • AvailabilityHigh
  • CWE References
  • NVD-CWE-noinfo
  • Technical References
  • Mozilla Bug Report #1861405
  • Vendor Resources
  • Mozilla Security Advisory MFSA-2023-51
  • Related CVEs
  • CVE-2026-6765: Mozilla Firefox Information Disclosure Flaw

  • CVE-2026-6782: Mozilla Firefox Information Disclosure Flaw

  • CVE-2026-6770: Firefox Information Disclosure Vulnerability

  • CVE-2026-6749: Mozilla Firefox Information Disclosure Bug
Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the World’s Most Advanced Cybersecurity Platform

See how our intelligent, autonomous cybersecurity platform can protect your organization now and into the future.

Try SentinelOne
  • Get Started
  • Get a Demo
  • Product Tour
  • Why SentinelOne
  • Pricing & Packaging
  • FAQ
  • Contact
  • Contact Us
  • Customer Support
  • SentinelOne Status
  • Language
  • Platform
  • Singularity Platform
  • Singularity Endpoint
  • Singularity Cloud
  • Singularity AI-SIEM
  • Singularity Identity
  • Singularity Marketplace
  • Purple AI
  • Services
  • Wayfinder TDR
  • SentinelOne GO
  • Technical Account Management
  • Support Services
  • Verticals
  • Energy
  • Federal Government
  • Finance
  • Healthcare
  • Higher Education
  • K-12 Education
  • Manufacturing
  • Retail
  • State and Local Government
  • Cybersecurity for SMB
  • Resources
  • Blog
  • Labs
  • Case Studies
  • Videos
  • Product Tours
  • Events
  • Cybersecurity 101
  • eBooks
  • Webinars
  • Whitepapers
  • Press
  • News
  • Ransomware Anthology
  • Company
  • About Us
  • Our Customers
  • Careers
  • Partners
  • Legal & Compliance
  • Security & Compliance
  • Investor Relations
  • S Foundation
  • S Ventures

©2026 SentinelOne, All Rights Reserved.

Privacy Notice Terms of Use

English