CVE-2016-6563 (GCVE-0-2016-6563)
Vulnerability from cvelistv5 – Published: 2018-07-13 20:00 – Updated: 2024-08-06 01:36
VLAI
EPSS
VEX
Title
D-Link DIR routers contain a stack-based buffer overflow in the HNAP Login action
Summary
Processing malformed SOAP messages when performing the HNAP Login action causes a buffer overflow in the stack in some D-Link DIR routers. The vulnerable XML fields within the SOAP body are: Action, Username, LoginPassword, and Captcha. The following products are affected: DIR-823, DIR-822, DIR-818L(W), DIR-895L, DIR-890L, DIR-885L, DIR-880L, DIR-868L, and DIR-850L.
Severity
9.8 (Critical)
CWE
Assigner
References
4 references
| URL | Tags |
|---|---|
| https://www.exploit-db.com/exploits/40805/ | exploitx_refsource_EXPLOIT-DB |
| https://www.kb.cert.org/vuls/id/677427 | third-party-advisoryx_refsource_CERT-VN |
| http://www.securityfocus.com/bid/94130 | vdb-entryx_refsource_BID |
| http://seclists.org/fulldisclosure/2016/Nov/38 | mailing-listx_refsource_FULLDISC |
Impacted products
9 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| D-Link | DIR-823 |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-822 |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-818L(W) |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-895L |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-890L |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-885L |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-880L |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-868L |
Unknown:
N/A
|
guessed | |
| D-Link | DIR-850L |
Unknown:
N/A
|
guessed |
Date Public
2016-11-07 00:00
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{
"lang": "en",
"value": "Processing malformed SOAP messages when performing the HNAP Login action causes a buffer overflow in the stack in some D-Link DIR routers. The vulnerable XML fields within the SOAP body are: Action, Username, LoginPassword, and Captcha. The following products are affected: DIR-823, DIR-822, DIR-818L(W), DIR-895L, DIR-890L, DIR-885L, DIR-880L, DIR-868L, and DIR-850L."
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],
"id": "CVE-2016-6563",
"lastModified": "2024-11-21T02:56:21.790",
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"source": "nvd@nist.gov",
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"published": "2018-07-13T20:29:01.003",
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}
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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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