CVE-2026-83549 (GCVE-0-2026-83549)
Vulnerability from cvelistv5 – Published: 2026-09-01 21:28 – Updated: 2026-09-21 13:07Summary
Post-authentication Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerability has been identified in the SMA1000 Appliance Management Console (AMC) which in specific conditions could potentially enable a remote authenticated attacker as administrator to execute arbitrary OS commands, resulting in remote code execution.
Severity
7.8 (High)
SSVC
Exploitation: active
Automatable: no
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-03 03:55 UTC
CWE
- CWE-78 - Improper neutralization of special elements used in an OS command ('OS command injection')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://psirt.global.sonicwall.com/vuln-detail/SN… | vendor-advisory |
| https://www.cisa.gov/known-exploited-vulnerabilit… | government-resource |
Impacted products
Date Public
2026-09-01 21:26
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 106b930f-4683-4444-9294-4ecc2e72b435
Exploited: Yes
Timestamps
First Seen: 2026-09-02
Asserted: 2026-09-02
Scope
Notes: SonicWall SMA1000 Appliances OS Command Injection Vulnerability | Affected: SonicWall / SMA1000 Appliances | Description: SonicWall SMA1000 Appliances contains an OS command injection vulnerability that could enable a remote authenticated attacker as administrator to execute arbitrary OS commands, resulting in remote code execution. | Required action: Apply mitigations in accordance with vendor instructions, ensuring compliance with CISA’s BOD 26-04 Prioritizing Security Updates Based on Risk (see URL in Notes) guidance and CISA’s “Forensics Triage Requirements” (see URL in Notes). Follow applicable BOD 26-04 guidance for cloud services or discontinue use of the product if mitigations are unavailable. Stakeholders are responsible for evaluating each asset's internet exposure and ensuring adherence to BOD 26-04 patching guidelines. | Due date: 2026-09-05 | Known ransomware campaign use (KEV): Unknown | Notes (KEV): https://psirt.global.sonicwall.com/vuln-detail/SNWLID-2026-0016 ; BOD 26-04: https://www.cisa.gov/news-events/directives/bod-26-04-prioritizing-security-updates-based-risk ; Forensics Triage Requirements: https://www.cisa.gov/news-events/directives/bod-26-04-implementation-guidance-prioritizing-security-updates-based-risk ; https://nvd.nist.gov/vuln/detail/CVE-2026-83549
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-78 |
|---|---|
| Feed | CISA Known Exploited Vulnerabilities Catalog |
| Product | SMA1000 Appliances |
| Due Date | 2026-09-05 |
| Date Added | 2026-09-02 |
| Vendorproject | SonicWall |
| Vulnerabilityname | SonicWall SMA1000 Appliances OS Command Injection Vulnerability |
| Knownransomwarecampaignuse | Unknown |
References
Created: 2026-09-02 18:00 UTC
| Updated: 2026-09-02 18:00 UTC
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 6701a3fe-0836-46a0-9862-641aaddec085
Exploited: Yes
Timestamps
First Seen: 2026-09-01
Asserted: 2026-09-01
Scope
Notes: Post-authentication Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerability has been identified in... | Affected: SonicWall / SMA1000 | CVSS: 7.8 (HIGH) | EPSS: 0.00917 | 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 | Post-authentication Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection') vulnerability has been identified in... |
| Vendor | SonicWall |
| Product | SMA1000 |
| Added Date | 2026-09-01T20:21:00.000Z |
| Cvss Score | 7.8 |
| Epss Score | 0.00917 |
| Cvss Severity | HIGH |
| Epss Percentile | 0.57798 |
| Used In Malware | unknown |
| Ahead Of Cisa Kev |
|
| Not Yet In Cisa Kev | False |
References
Created: 2026-09-02 21:00 UTC
| Updated: 2026-09-02 21:00 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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