CVE-2024-44309
XSS in Apple Ipados ≤ 17.7.2
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:L/I:L/A:LSummary
CVE-2024-44309 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Apple Ipados. Its CVSS base score is 6.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 2% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
A cookie management issue was addressed with improved state management in multiple Apple products, resulting in a cross-site scripting vulnerability tracked as CVE-2024-44309 and CWE-79. Affected software includes versions of Safari prior to 18.1.1, iOS and iPadOS prior to 17.7.2 and 18.1.1, macOS Sequoia prior to 15.1.1, and visionOS prior to 2.1.1. The flaw carries a CVSS 3.1 score of 6.3 reflecting network attack vector, low complexity, and no required privileges.
An unauthenticated remote attacker can exploit the issue when a user processes maliciously crafted web content, achieving limited cross-site scripting effects that impact confidentiality, integrity, and availability.
Apple security advisories for the listed updates recommend installing the patches for Safari 18.1.1, iOS 17.7.2, iOS 18.1.1, macOS Sequoia 15.1.1, and visionOS 2.1.1 to resolve the cookie state management weakness.
Apple has stated that the vulnerability may have been actively exploited on Intel-based Mac systems. The associated EPSS score remains low with only minor movement between its current value of 0.0094 and peak of 0.0131.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-41208
Vulnerability Data
A cookie management issue was addressed with improved state management. This issue is fixed in Safari 18.1.1, iOS 17.7.2 and iPadOS 17.7.2, iOS 18.1.1 and iPadOS 18.1.1, macOS Sequoia 15.1.1, visionOS 2.1.1. Processing maliciously crafted web content may lead to…
more
a cross site scripting attack. Apple is aware of a report that this issue may have been actively exploited on Intel-based Mac systems.
- CWE(s)
- KEV Date Added
- 21 November 2024
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.