CVE-2026-83548 (GCVE-0-2026-83548)
Vulnerability from cvelistv5 – Published: 2026-09-01 21:25 – Updated: 2026-09-03 03:55Summary
A Pre-authentication SSRF vulnerability exists in the SMA1000 Appliance Work Place interface due to an unintended alternate access path. A remote unauthenticated attacker could potentially exploit this vulnerability to gain unauthorized access to sensitive functionality and perform unauthorized operations.
Severity
10 (Critical)
SSVC
Exploitation: active
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-01 00:00 UTC
CWE
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 21:17
CISA
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 300a00f0-a093-48eb-a8c6-db9f1e6680bf
Exploited: Yes
Timestamps
First Seen: 2026-09-02
Asserted: 2026-09-02
Scope
Notes: SonicWall SMA1000 Appliances Server-Side Request Forgery Vulnerability | Affected: SonicWall / SMA1000 Appliances | Description: SonicWall SMA1000 Appliances contains a server-side request forgery vulnerability that could allow a remote unauthenticated attacker to gain unauthorized access to sensitive functionality and perform unauthorized operations. | 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-2026-83548
Evidence
Type: Vendor Report
Signal: Successful Exploitation
Confidence: 80%
Source: cisa-kev
Details
| Cwes | CWE-918 CWE-441 |
|---|---|
| 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 Server-Side Request Forgery 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: eac69f1f-e80f-47d4-8cd2-0b7faaf47fdf
Exploited: Yes
Timestamps
First Seen: 2026-09-01
Asserted: 2026-09-01
Scope
Notes: A Pre-authentication SSRF vulnerability exists in the SMA1000 Appliance Work Place interface due to an unintended alternate access path. A remote... | Affected: SonicWall / SMA1000 | CVSS: 10.0 (CRITICAL) | EPSS: 0.00266 | 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 | A Pre-authentication SSRF vulnerability exists in the SMA1000 Appliance Work Place interface due to an unintended alternate access path. A remote... |
| Vendor | SonicWall |
| Product | SMA1000 |
| Added Date | 2026-09-01T20:19:00.000Z |
| Cvss Score | 10.0 |
| Epss Score | 0.00266 |
| Cvss Severity | CRITICAL |
| Epss Percentile | 0.18174 |
| 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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