CVE-2017-9822 (GCVE-0-2017-9822)
Vulnerability from cvelistv5 – Published: 2017-07-20 12:00 – Updated: 2025-10-21 23:55Summary
DNN (aka DotNetNuke) before 9.1.1 has Remote Code Execution via a cookie, aka "2017-08 (Critical) Possible remote code execution on DNN sites."
Severity
8.8 (High)
SSVC
Exploitation: active
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-02-07 13:41 UTC
CWE
- Remote Code Execution via untrusted deserialization of Xml data
- CWE-94 - Improper Control of Generation of Code ('Code Injection')
Assigner
References
4 references
| URL | Tags |
|---|---|
| http://www.securityfocus.com/bid/102213 | vdb-entryx_refsource_BID |
| http://www.dnnsoftware.com/community/security/sec… | x_refsource_CONFIRM |
| http://packetstormsecurity.com/files/157080/DotNe… | x_refsource_MISC |
| https://www.cisa.gov/known-exploited-vulnerabilit… | government-resource |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| DotNetNuke | DotNetNuke CMS Fixed in 9.1.1 |
Affected:
DotNetNuke CMS Fixed in 9.1.1
|
guessed |
Date Public
2017-07-20 00:00
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: c6d0e65b-dbfa-41fd-b940-c44b92d4779b
Exploited: Yes
Timestamps
First Seen: 2021-11-03
Asserted: 2021-11-03
Scope
Notes: KEV entry: DotNetNuke (DNN) Remote Code Execution Vulnerability | Affected: DotNetNuke (DNN) / DotNetNuke (DNN) | Description: DotNetNuke (DNN) contains a vulnerability that may allow for remote code execution via cookie deserialization. | Required action: Apply updates per vendor instructions. | Due date: 2022-05-03 | Known ransomware campaign use (KEV): Known | Notes (KEV): https://nvd.nist.gov/vuln/detail/CVE-2017-9822
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-20 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | DotNetNuke (DNN) |
| Due Date | 2022-05-03 |
| Date Added | 2021-11-03 |
| Vendorproject | DotNetNuke (DNN) |
| Vulnerabilityname | DotNetNuke (DNN) Remote Code Execution Vulnerability |
| Knownransomwarecampaignuse | Known |
References
Created: 2026-02-02 13:26 UTC
| Updated: 2026-02-06 07:53 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 30f9cf14-9eec-4b17-8dba-9b9fc120ed22
Exploited: Yes
Timestamps
First Seen: 2021-11-03
Asserted: 2021-11-03
Scope
Notes: KEVIntel entry: DNN (aka DotNetNuke) before 9.1.1 has Remote Code Execution via a cookie, aka "2017-08 (Critical) Possible remote code execution on DNN sites." | Affected: DotNetNuke / DotNetNuke CMS Fixed in 9.1.1 | CVSS: 8.8 (HIGH) | Used in malware: yes | Not yet in CISA KEV: False
Evidence
Type: Public Report
Signal: Confirmed Compromise
Confidence: 70%
Source: kevintel
Details
| Feed | KEVIntel (kevintel.com) |
|---|---|
| Title | DNN (aka DotNetNuke) before 9.1.1 has Remote Code Execution via a cookie, aka "2017-08 (Critical) Possible remote code execution on DNN sites." |
| Vendor | DotNetNuke |
| Product | DotNetNuke CMS Fixed in 9.1.1 |
| Added Date | 2021-11-03T00:00:00.000Z |
| Cvss Score | 8.8 |
| Epss Score | None |
| Cvss Severity | HIGH |
| Epss Percentile | None |
| Used In Malware | yes |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | False |
References
Created: 2026-06-23 11:13 UTC
| Updated: 2026-06-23 11:13 UTC
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"url": "http://www.dnnsoftware.com/community/security/security-center"
},
{
"name": "http://packetstormsecurity.com/files/157080/DotNetNuke-Cookie-Deserialization-Remote-Code-Execution.html",
"refsource": "MISC",
"url": "http://packetstormsecurity.com/files/157080/DotNetNuke-Cookie-Deserialization-Remote-Code-Execution.html"
}
]
}
}
}
},
"cveMetadata": {
"assignerOrgId": "eb103674-0d28-4225-80f8-39fb86215de0",
"assignerShortName": "hpe",
"cveId": "CVE-2017-9822",
"datePublished": "2017-07-20T12:00:00.000Z",
"dateReserved": "2017-06-22T00:00:00.000Z",
"dateUpdated": "2025-10-21T23:55:36.233Z",
"state": "PUBLISHED"
},
"dataType": "CVE_RECORD",
"dataVersion": "5.1"
}
}
}
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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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