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CVE-2026-81524 MongoDB CVE debrief

CVE-2026-81524 debrief based on the supplied source corpus. The CVE record was published on 2026-08-27T20:18:50.773Z and has not been modified since then. The weakness in the MongoDB C Driver allows special elements in caller-supplied database and collection name components to pass without sanitization, potentially directing operations at unintended resources. Defenders and developers of applications that incorporate untrusted input into these components should assess exposure and prioritize patching and verification.

Vendor
MongoDB
Product
C Driver
CVSS
MEDIUM 5.3
CISA KEV
Not listed in stored evidence
Original CVE published
2026-08-27
Original CVE updated
2026-09-29
Advisory published
2026-08-27
Advisory updated
2026-09-29

Who should care

Defenders and developers of applications that incorporate untrusted input into database and collection name components using the MongoDB C Driver should assess exposure and prioritize patching and verification.

Why it matters

CVE-2026-81524 is a weakness in the MongoDB C Driver that allows special elements in caller-supplied database and collection name components to pass without sanitization, potentially directing operations at unintended resources. Defenders and developers of applications that incorporate untrusted input into these components should assess exposure and prioritize patching and verification.

  • Verify and apply patches for the MongoDB C Driver to prevent potential exploitation.
  • Review and update applications to ensure proper sanitization of database and collection name components.
  • Monitor for potential exploitation attempts targeting the MongoDB C Driver weakness.

Technical summary

The MongoDB C Driver has a weakness that allows special elements in caller-supplied database and collection name components to pass without sanitization, potentially directing operations at unintended resources. This weakness can be exploited by an attacker to access unauthorized data or perform malicious actions. The vulnerability is due to a lack of proper input validation and sanitization in the MongoDB C Driver. An application that incorporates untrusted input into these name components can have operations directed at a resource other than the one intended.

Defensive priority

Defenders should prioritize verifying and applying patches for the MongoDB C Driver, especially in applications that incorporate untrusted input into database and collection name components.

Recommended defensive actions

  • Verify and apply patches for the MongoDB C Driver, especially in applications that incorporate untrusted input into database and collection name components.
  • Review and update applications that use the MongoDB C Driver to ensure proper sanitization of database and collection name components.
  • Monitor for potential exploitation attempts targeting the MongoDB C Driver weakness.
  • Perform a thorough review of the application code to identify and address potential vulnerabilities.
  • Implement additional security measures, such as input validation and sanitization, to prevent similar attacks.
  • Conduct regular security audits and penetration testing to identify potential weaknesses.
  • Develop and implement a incident response plan in case of a potential exploit.

Evidence notes

The CVE record and NVD entry provide details on the weakness in the MongoDB C Driver, allowing special elements in caller-supplied database and collection name components to pass without sanitization.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-81524 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-81524

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-81524 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-81524

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

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.