Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:NSummary
CVE-2012-0767 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Adobe Flash Player. Its CVSS base score is 6.1 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 7% of CVEs by exploit likelihood; CISA has added it to the Known Exploited Vulnerabilities catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
The vulnerability is a cross-site scripting flaw, tracked as CWE-79 and described as a Universal XSS issue, that exists in Adobe Flash Player. It affects versions prior to 10.3.183.15 and 11.x prior to 11.1.102.62 on Windows, Mac OS X, Linux, and Solaris; versions prior to 11.1.111.6 on Android 2.x and 3.x; and versions prior to 11.1.115.6 on Android 4.x. The flaw permits injection of arbitrary web script or HTML through unspecified vectors and carries a CVSS 3.1 score of 6.1.
Remote attackers can exploit the issue without authentication by delivering malicious content that leverages the Flash Player component, resulting in script execution in the context of the affected site. The vulnerability was actively exploited in the wild during February 2012.
Vendor advisories such as RHSA-2012-0144, openSUSE and Gentoo security announcements, and Secunia alerts address the issue through updated Flash Player packages that remediate the input-handling weakness. The real-world exploitation noted in the CVE record indicates immediate operational impact on any unpatched installations at the time of disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2012-0799
Vulnerability Data
Cross-site scripting (XSS) vulnerability in Adobe Flash Player before 10.3.183.15 and 11.x before 11.1.102.62 on Windows, Mac OS X, Linux, and Solaris; before 11.1.111.6 on Android 2.x and 3.x; and before 11.1.115.6 on Android 4.x allows remote attackers to inject…
more
arbitrary web script or HTML via unspecified vectors, aka "Universal XSS (UXSS)," as exploited in the wild in February 2012.
- CWE(s)
- KEV Date Added
- 08 June 2022
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.