CVE-2017-7876 (GCVE-0-2017-7876)
Vulnerability from cvelistv5 – Published: 2017-06-15 20:00 – Updated: 2024-08-05 16:19Summary
This command injection vulnerability in QTS allows attackers to run arbitrary commands in the compromised application. QNAP have already fixed the issue in QTS 4.2.6 build 20170517, QTS 4.3.3.0174 build 20170503 and later versions.
Severity
10 (Critical)
CWE
- n/a
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://www.qnap.com/en/release-notes/qts/4.3.3.0… | x_refsource_MISC |
| https://www.qnap.com/en/release-notes/qts/4.2.6/2… | x_refsource_MISC |
| https://www.qnap.com/zh-tw/security-advisory/nas-… | x_refsource_MISC |
Date Public
2017-06-15 00:00
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 78f5676b-e9fb-4677-aaf3-240da91541ff
Exploited: Yes
Characteristics
Severity:
98.0
Timestamps
First Seen: 2023-10-16
Asserted: 2023-10-16
Last Seen: 2023-10-16
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: QNAP / QNAP QTS | Class: nas | Severity: Critical (CVSS 9.8) | IoT: yes | In CISA KEV: no | Honeypot connections on 2023-09-23: 946
Evidence
Type: Honeypot
Signal: In The Wild Attempts
Confidence: 70%
Source: shadowserver
Details
| 1D | 1 |
|---|---|
| Iot | yes |
| Feed | Shadowserver Foundation honeypot/exploited-vulnerabilities |
| Type | http-scan |
| Class | nas |
| 7D Avg | 0 |
| Vendor | QNAP |
| 30D Avg | 0 |
| 90D Avg | 0 |
| Product | QNAP QTS |
| Cisa Kev | no |
| Connections | 946 |
| Observation Date | 2023-09-23 |
| Vulnerability Class | CVSS |
| Vulnerability Score | 9.8 |
| Vulnerability Severity | Critical |
References
Created: 2026-06-30 14:18 UTC
| Updated: 2026-06-30 15:15 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 86ee8f0e-a6d3-48ba-8cc5-d1b5a5609e46
Exploited: Yes
Timestamps
First Seen: 2026-09-15
Asserted: 2026-09-15
Scope
Notes: This command injection vulnerability in QTS allows attackers to run arbitrary commands in the compromised application. QNAP have already fixed the... | Affected: Qnap / QTS | CVSS: 10.0 (CRITICAL) | EPSS: 0.03338 | Used in malware: unknown | Not yet in CISA KEV: True
Evidence
Type: Public Report
Signal: Successful Exploitation
Confidence: 70%
Source: previdian
Details
| Feed | Previdian (previdian.com) |
|---|---|
| Title | This command injection vulnerability in QTS allows attackers to run arbitrary commands in the compromised application. QNAP have already fixed the... |
| Cve Id | CVE-2017-7876 |
| Vendor | Qnap |
| Ghsa Id | None |
| Product | QTS |
| Added Date | 2026-09-15T00:00:00.000Z |
| Cvss Score | 10.0 |
| Epss Score | 0.03338 |
| Previous Ids | |
| Cvss Severity | CRITICAL |
| Virtual Patch | False |
| Cvss Estimated | False |
| Epss Percentile | 0.8798 |
| Used In Malware | unknown |
| Vulnerability Id | CVE-2017-7876 |
| Ahead Of Cisa Kev | None |
| Not Yet In Cisa Kev | True |
References
Created: 2026-09-16 11:00 UTC
| Updated: 2026-09-16 11:00 UTC
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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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