Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2024-46538 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Netgate Pfsense. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 0.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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.
CVE-2024-46538 is a stored cross-site scripting vulnerability in pfSense version 2.5.2. The flaw resides in the interfaces_groups_edit.php page, where unsanitized input supplied to the $pconfig variable is later rendered without proper encoding, allowing arbitrary HTML or JavaScript to be injected into the administrative web interface.
An authenticated administrator can exploit the issue by submitting a crafted payload that is stored and subsequently executed in the browsers of other users who view the affected page. Successful exploitation yields the ability to perform actions within the pfSense web GUI under the context of the victim account, such as modifying interface group settings or exfiltrating session data, though the attack requires high privileges and user interaction.
The EPSS score for this vulnerability stands at 0.8365 with no material increase from a lower baseline after disclosure. Public references include a detailed technical write-up on GitHub and the corresponding pfSense Redmine issue tracker entry.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-41866
Vulnerability Data
A cross-site scripting (XSS) vulnerability in pfsense v2.5.2 allows attackers to execute arbitrary web scripts or HTML via a crafted payload injected into the $pconfig variable at interfaces_groups_edit.php.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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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.