Cyber Resilience

CVE-2025-6709

High

Published: 26 June 2025

Published
26 June 2025
Modified
15 September 2025
KEV Added
Patch
CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0043 62.7th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2025-6709 is a high-severity Improper Input Validation (CWE-20) vulnerability in Mongodb Mongodb. Its CVSS base score is 7.5 (High).

Operationally, ranked in the top 37.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

The MongoDB Server is susceptible to a denial of service vulnerability due to improper handling of specific date values in JSON input when using OIDC authentication. This can be reproduced using the mongo shell to send a malicious JSON payload…

more

leading to an invariant failure and server crash. This issue affects MongoDB Server v7.0 versions prior to 7.0.17 and MongoDB Server v8.0 versions prior to 8.0.5. The same issue affects MongoDB Server v6.0 versions prior to 6.0.21, but an attacker can only induce denial of service after authenticating.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

mongodb
mongodb
6.0.0 — 6.0.21 · 7.0.0 — 7.0.17 · 8.0.0 — 8.0.5

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

addresses: CWE-20

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

addresses: CWE-20

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

addresses: CWE-20

Directly implements checks on information inputs to reject invalid data before processing.

addresses: CWE-20

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

References