CVE-2017-2983 (GCVE-0-2017-2983)
Vulnerability from cvelistv5 – Published: 2017-03-14 16:00 – Updated: 2024-08-05 14:09
VLAI
EPSS
VEX
Summary
Adobe Shockwave versions 12.2.7.197 and earlier have an insecure library loading (DLL hijacking) vulnerability. Successful exploitation could lead to escalation of privilege.
Severity
7.8 (High)
CWE
- Insecure Library Loading (DLL hijacking)
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://helpx.adobe.com/security/products/shockwa… | x_refsource_CONFIRM |
| http://www.securityfocus.com/bid/96863 | vdb-entryx_refsource_BID |
| http://www.securitytracker.com/id/1037993 | vdb-entryx_refsource_SECTRACK |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | Adobe Shockwave 12.2.7.197 and earlier. |
Affected:
Adobe Shockwave 12.2.7.197 and earlier.
|
Date Public
2017-03-14 00:00
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
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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.