Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:H/I:H/A:NSummary
CVE-2023-39511 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Fedoraproject Fedora. Its CVSS base score is 6.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked at the 49th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-43233
Vulnerability Data
Cacti is an open source operational monitoring and fault management framework. Affected versions are subject to a Stored Cross-Site-Scripting (XSS) Vulnerability which allows an authenticated user to poison data stored in the _cacti_'s database. These data will be viewed by…
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administrative _cacti_ accounts and execute JavaScript code in the victim's browser at view-time. The script under `reports_admin.php` displays reporting information about graphs, devices, data sources etc. _CENSUS_ found that an adversary that is able to configure a malicious device name, related to a graph attached to a report, can deploy a stored XSS attack against any super user who has privileges of viewing the `reports_admin.php` page, such as administrative accounts. A user that possesses the _General Administration>Sites/Devices/Data_ permissions can configure the device names in _cacti_. This configuration occurs through `http://<HOST>/cacti/host.php`, while the rendered malicious payload is exhibited at `http://<HOST>/cacti/reports_admin.php` when the a graph with the maliciously altered device name is linked to the report. This issue has been addressed in version 1.2.25. Users are advised to upgrade. Users unable to upgrade should manually filter HTML output.
- 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
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.