PatchSiren cyber security CVE debrief
CVE-2026-36777 Shenzhen Tenda Technology Co., Ltd CVE debrief
A stack overflow vulnerability was discovered in the Tenda W3 Wireless Router v1.0.0.3(2204) in the param_1 parameter of the formSetCfm function. This issue allows attackers to cause a Denial of Service (DoS) via a crafted HTTP request. The vulnerability has a CVSS score of 6.5 and a severity of MEDIUM.
- Vendor
- Shenzhen Tenda Technology Co., Ltd
- Product
- Tenda W3 Wireless Router
- CVSS
- MEDIUM 6.5
- CISA KEV
- Not listed in stored evidence
- Original CVE published
- 2026-06-09
- Original CVE updated
- 2026-07-20
- Advisory published
- 2026-06-09
- Advisory updated
- 2026-07-20
Who should care
Users of Shenzhen Tenda Technology Co., Ltd Tenda W3 Wireless Router v1.0.0.3(2204) should be aware of this vulnerability and take necessary actions to mitigate the risk.
Technical summary
The vulnerability is caused by a stack overflow in the param_1 parameter of the formSetCfm function. This can be exploited by sending a crafted HTTP request to the affected device, potentially leading to a Denial of Service (DoS).
Defensive priority
MEDIUM
Recommended defensive actions
- Apply patches or updates provided by the vendor, if available.
- Restrict access to the affected device and limit the attack surface.
- Monitor network traffic and system logs for suspicious activity.
Evidence notes
The CVE record and NVD detail can be found at [cve-org] and [nvd], respectively. Additional information can be found at [ref-4].
Sources and references
Verified primary and authoritative sources
-
CVE-2026-36777 CVE Program record
Publisher, destination, and source semantics verified
URL: https://www.cve.org/CVERecord?id=CVE-2026-36777
CVE Program - Official CVE Program record with source-provided CVE metadata.
-
CVE-2026-36777 NVD vulnerability detail
Publisher, destination, and source semantics verified
URL: https://nvd.nist.gov/vuln/detail/CVE-2026-36777
NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.
Supplemental references
-
Source reference
Unverified legacy reference
URL: https://github.com/xhh0124/SemVulLLM/tree/main/W3/formSetCfm
Methodology and review provenance
AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.