Cyber Resilience

CVE-2023-0436

Info Disclosure in Mongodb Atlas Kubernetes Operator 1.6.0 – 1.7.1

Published
07 November 2023
Modified
21 November 2024
Patch / advisory
CVSS Score v3.1 4.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:H/I:N/A:N
EPSS Score 0.0060 46th percentile
Risk Priority 37 floored blend · peak EPSS

Summary

CVE-2023-0436 is a medium-severity Insertion of Sensitive Information into Log File (CWE-532) vulnerability in Mongodb Atlas Kubernetes Operator. Its CVSS base score is 4.5 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Unsecured Credentials (T1552); ranked at the 46th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

OWASP Top 10 for Web (2025)

EU & UK References

Vulnerability Data

The affected versions of MongoDB Atlas Kubernetes Operator may print sensitive information like GCP service account keys and API integration secrets while DEBUG mode logging is enabled. This issue affects MongoDB Atlas Kubernetes Operator versions: 1.5.0, 1.6.0, 1.6.1, 1.7.0. Please…

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note that this is reported on an EOL version of the product, and users are advised to upgrade to the latest supported version. Required Configuration: DEBUG logging is not enabled by default, and must be configured by the end-user. To check the log-level of the Operator, review the flags passed in your deployment configuration (eg. https://github.com/mongodb/mongodb-atlas-kubernetes/blob/main/config/manager/manager.yaml#L27 https://github.com/mongodb/mongodb-atlas-kubernetes/blob/main/config/manager/manager.yaml#L27 )

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1552 Unsecured Credentials Credential Access
Adversaries may search compromised systems to find and obtain insecurely stored credentials.
T1552.001 Credentials In Files Credential Access
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
T1654 Log Enumeration Discovery
Adversaries may enumerate system and service logs to find useful data.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2026-8200Same vendor: Mongodb
CVE-2026-9751Same vendor: Mongodb
CVE-2025-6711Same vendor: Mongodb
CVE-2026-9735Same vendor: Mongodb
CVE-2023-26207Shared CWE-532
CVE-2023-35695Shared CWE-532
CVE-2024-52940Shared CWE-532
CVE-2024-48852Shared CWE-532
CVE-2025-6392Shared CWE-532
CVE-2025-51497Shared CWE-532

Affected Assets

mongodb
atlas kubernetes operator
1.5.0 · 1.6.0 — 1.7.1

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-532

Procedures mandate excluding sensitive data from logs to prevent unauthorized exposure via audit records.

addresses: CWE-532

Identifies insertion of sensitive data into logs, allowing detection of unauthorized disclosure.

addresses: CWE-532

Cross-organizational coordination enables agreement on what data to include in audit logs, directly reducing insertion of sensitive information.

addresses: CWE-532

Identifying logging as a data action allows prevention of sensitive information being inserted into log files.

addresses: CWE-532

The process of identifying and eradicating spilled information applies directly to sensitive data inserted into log files.

addresses: CWE-532

Specific processing rules for sensitive PII categories commonly include restrictions on logging, making insertion of such data into log files less likely.

addresses: CWE-532

PIAs detect planned or existing logging of PII and require removal or protection, preventing insertion of sensitive information into logs.

addresses: CWE-532

Limits insertion of sensitive operational details into logs by treating such data as key information requiring protection.

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.PS-06 mostly match
prevents

Secure SDLC practices directly prohibit writing sensitive data to logs; eliminating the weakness satisfies only one narrow slice of the control.

PR.PS-04 partial match
prevents

Log generation configuration can and should exclude sensitive data, but the control statement focuses on availability rather than content filtering.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.8.15 Logging mostly match
prevents

Requiring de-identification and privacy controls before logs leave the organization reduces the chance that sensitive data inadvertently captured in logs becomes exposed to external parties.

mitigates

By defining what records must be kept, where, and for how long, the control discourages the inadvertent inclusion of sensitive information in logs or other externally accessible files that fall outside the formal record system.

mitigates

Mandating deletion of temporary files and logs that may contain sensitive information prevents those artifacts from remaining accessible after the data is no longer needed.

A.8.11 Data masking partial match
mitigates

When log entries are produced from masked data sets, the control prevents the inadvertent insertion of sensitive values into externally accessible log files.

mitigates

DLP inspection of logs and file transfers can detect and block the inadvertent placement of sensitive tokens or credentials into externally accessible log files before they are written or transmitted.

prevents

Requiring restrictions on free-text fields and proper error-message handling stops developers from embedding or leaking sensitive data into logs or diagnostic output.

References