CVE-2015-0310 (GCVE-0-2015-0310)
Vulnerability from cvelistv5 – Published: 2015-01-23 21:00 – Updated: 2025-11-17 20:10Summary
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, and have an unspecified impact on other platforms, via unknown vectors, as exploited in the wild in January 2015.
Severity
7.8 (High)
SSVC
Exploitation: active
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-11-17 20:07 UTC
CWE
- n/a
- CWE-200 - Exposure of Sensitive Information to an Unauthorized Actor
Assigner
References
10 references
| URL | Tags |
|---|---|
| http://security.gentoo.org/glsa/glsa-201502-02.xml | vendor-advisoryx_refsource_GENTOO |
| http://www.securityfocus.com/bid/72261 | vdb-entryx_refsource_BID |
| http://secunia.com/advisories/62660 | third-party-advisoryx_refsource_SECUNIA |
| http://secunia.com/advisories/62740 | third-party-advisoryx_refsource_SECUNIA |
| http://www.securitytracker.com/id/1031609 | vdb-entryx_refsource_SECTRACK |
| http://helpx.adobe.com/security/products/flash-pl… | x_refsource_CONFIRM |
| http://secunia.com/advisories/62452 | third-party-advisoryx_refsource_SECUNIA |
| http://secunia.com/advisories/62601 | third-party-advisoryx_refsource_SECUNIA |
| https://www.cisa.gov/known-exploited-vulnerabilit… | government-resource |
| https://github.com/cisagov/vulnrichment/issues/196 | issue-tracking |
Date Public
2015-01-22 00:00
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: c55fd450-101b-457d-b402-3bb35c2d5aa9
Exploited: Yes
Timestamps
First Seen: 2022-05-25
Asserted: 2022-05-25
Scope
Notes: Adobe Flash Player ASLR Bypass Vulnerability | Affected: Adobe / Flash Player | Description: Adobe Flash Player does not properly restrict discovery of memory addresses, which allows attackers to bypass the address space layout randomization (ASLR) protection mechanism. | Required action: The impacted product is end-of-life and should be disconnected if still in use. | Due date: 2022-06-15 | Known ransomware campaign use (KEV): Unknown | Notes (KEV): https://nvd.nist.gov/vuln/detail/CVE-2015-0310
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-264 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | Flash Player |
| Due Date | 2022-06-15 |
| Date Added | 2022-05-25 |
| Vendorproject | Adobe |
| Vulnerabilityname | Adobe Flash Player ASLR Bypass Vulnerability |
| Knownransomwarecampaignuse | Unknown |
References
Created: 2026-10-02 08:09 CEST
| Updated: 2026-10-02 08:09 CEST
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 8191e087-8789-4c19-af7c-fbe78dc9d166
Exploited: Yes
Timestamps
First Seen: 2022-05-25
Asserted: 2022-05-25
Scope
Notes: 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... | Affected: Adobe / Flash Player | CVSS: 7.8 (HIGH) | EPSS: 0.15097 | Used in malware: unknown | Not yet in CISA KEV: False
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | 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... |
| Cve Id | CVE-2015-0310 |
| Vendor | Adobe |
| Ghsa Id | None |
| Product | Flash Player |
| Added Date | 2022-05-25T00:00:00.000Z |
| Cvss Score | 7.8 |
| Epss Score | 0.15097 |
| Previous Ids | |
| Cvss Severity | HIGH |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.96636 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2015-0310 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | False |
References
Created: 2026-10-02 09:11 CEST
| Updated: 2026-10-02 09:11 CEST
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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