Raw vector
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:HCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2015-0310 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Adobe Flash Player. Its CVSS base score is 7.8 (High).
Operationally, ranked in the top 3% 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.
Adobe Flash Player versions prior to 13.0.0.262, 14.x through 16.x prior to 16.0.0.287 on Windows and OS X, and prior to 11.2.202.438 on Linux contain a flaw that fails to properly restrict discovery of memory addresses. This weakness is tracked under CVE-2015-0310 with a CVSS 3.1 base score of 7.8 and is associated with CWE-200 information disclosure.
Attackers can leverage the issue through unknown vectors to bypass ASLR on Windows systems and obtain an unspecified impact on other platforms. The vulnerability was actively exploited in the wild during January 2015, enabling local attackers with the ability to supply crafted Flash content to weaken memory protections and facilitate further compromise.
Adobe addressed the flaw in security bulletin APSB15-02, which provides updated Flash Player builds for all affected platforms; multiple Secunia advisories also reference the same remediation steps and urge immediate application of the patches. The issue saw real-world exploitation shortly after disclosure, underscoring the need for rapid deployment of the vendor fixes.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2015-0323
Vulnerability Data
Adobe Flash Player before 13.0.0.262 and 14.x through 16.x before 16.0.0.287 on Windows and OS X and before 11.2.202.438 on Linux does not properly restrict discovery of memory addresses, which allows attackers to bypass the ASLR protection mechanism on Windows,…
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and have an unspecified impact on other platforms, via unknown vectors, as exploited in the wild in January 2015.
- CWE(s)
- KEV Date Added
- 25 May 2022
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
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.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.
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.
A.5.10 only requires awareness, a topic-specific acceptable-use policy stating expected behaviours/monitoring, and procedures referencing classification and other controls; per the owner's explicit rule on labelling and similar dependency-style clauses, this does not itself prevent exposure (CWE-200) unless access/DLP/etc. act on it.
Requiring the return of all physical and electronic assets plus secure deletion of organizational data from personal devices reduces the chance that sensitive information remains accessible to departing personnel.
A.5.12 only defines and communicates a classification scheme so that protection needs can be understood; per the owner's explicit rule, labeling/classification does not itself prevent exposure and requires other controls (e.g. access enforcement) to act on it.
By requiring classification labels and metadata on all information assets, the control makes it harder for sensitive data to be inadvertently exposed because downstream systems and users can recognize and enforce handling rules based on those labels.
Requiring encryption, access controls, and recipient authentication for transfers directly reduces the chance that sensitive data reaches an unauthorized observer.
Secure delivery, protected storage, and confidentiality of allocation records limit exposure of authentication material to unauthorized observers.
Hardening callouts derived
DISA STIG baselines are authored against specific weaknesses. Where this CVE cites a broad weakness class, the mapping is not asserted at that abstraction (owner ruling, 2026-09-25: grade only at Base and below), so no rule is shown here rather than a rule shown against the wrong grain.