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CVE Record

CVE-2026-23529: Arbitrary File Read in Google BigQuery Sink connector

Kafka Connect BigQuery Connector is an implementation of a sink connector from Apache Kafka to Google BigQuery. Prior to 2.11.0, there is an arbitrary file read in Google BigQuery Sink connector. Aiven's Google BigQuery Kafka Connect Sink connector requires Google Cloud credential configurations for authentication to BigQuery services. During connector configuration, users can supply credential JSON files that are processed by Google authentication libraries. The service fails to validate externally-sourced credential configurations before passing them to the authentication libraries. An attacker can exploit this by providing a malicious credential configuration containing crafted credential_source.file paths or credential_source.url endpoints, resulting in arbitrary file reads or SSRF attacks.

HighCVSS 7.7Not KEV-listedUpdated
Glexia's TakeAutomated analysishigh

Security readout for executives and security teams

Plain-English summary

CVE-2026-23529 affects Aiven’s BigQuery Kafka Connect Sink connector before 2.11.0. A user who can submit connector configuration may cause the service to read unintended files or make server-side requests through crafted Google credential settings. The main business risk is exposure of sensitive local data or internal services from systems running the connector.

Executive priority

Treat as a high-priority platform remediation if this connector is deployed. Prioritize shared or self-service Kafka Connect environments first, because the issue depends on who can submit connector configuration and what files or internal endpoints the connector runtime can reach.

Technical view

The connector passes externally supplied Google Cloud credential configuration to Google authentication libraries without sufficient validation. Crafted credential_source.file paths may trigger arbitrary file reads, and credential_source.url endpoints may enable SSRF. The CVSS 3.1 score is 7.7, requiring low privileges, no user interaction, network access, changed scope, and high confidentiality impact.

Likely exposure

Exposure is most likely where Apache Kafka Connect deployments use Aiven-Open bigquery-connector-for-apache-kafka versions earlier than 2.11.0 and allow users, tenants, or automation to create or modify BigQuery sink connector configurations.

Exploitation context

The CVE record does not indicate known active exploitation, and KEV status is false. Exploitation requires privilege to provide or alter connector configuration, but that may be realistic in shared Kafka Connect environments, CI/CD-managed connector deployments, or multi-team data platforms.

Researcher notes

Evidence identifies CWE-73 and CWE-918. The public advisory and CVE describe the issue class and fixed version, but the bundle does not provide active exploitation evidence. Validate impact by reviewing configuration trust boundaries and connector runtime access rather than attempting offensive reproduction.

Mitigation direction

  • Upgrade bigquery-connector-for-apache-kafka to version 2.11.0 or later.
  • Restrict connector creation and configuration changes to trusted administrators.
  • Review existing BigQuery sink connector credential configuration sources.
  • Follow Aiven and Google guidance for any additional hardening recommendations.

Validation and detection

  • Inventory Kafka Connect clusters using the Aiven BigQuery sink connector.
  • Confirm connector versions are 2.11.0 or later.
  • Review access controls for connector configuration APIs and deployment pipelines.
  • Check connector configs for externally sourced credential file or URL references.
Prepared
Confidence
high
Sources
6

Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.

Potential ATT&CK relevance

Conservative CVE-to-ATT&CK context

These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.

ATT&CK lookup starting points

Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.

cwe · medium confidence lookup

CWE-73: File access and web shell behavior lookup

File traversal and upload weaknesses can lead teams to review file, web shell, execution, and collection telemetry. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.

Open ATT&CK lookup
cwe · medium confidence lookup

CWE-918: Information exposure and cloud metadata lookup

Information exposure and SSRF weaknesses can make discovery, cloud metadata, and credential material review relevant. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.

Open ATT&CK lookup
description · low confidence lookup

Credential and access behavior lookup

The CVE wording references authentication or credential exposure, so valid-account and credential-access review may help. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.

Open ATT&CK lookup
description · low confidence lookup

Cloud metadata behavior lookup

The CVE wording references SSRF or metadata access, so cloud discovery and credential material review may help. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.

Open ATT&CK lookup
description · low confidence lookup

File access behavior lookup

The CVE wording references file access or upload behavior, so file telemetry and web shell review may help. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.

Open ATT&CK lookup
cve · low confidence lookup

CVE-2026-23529 mapping review

Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.

Open ATT&CK lookup
Vulnerability profileCVE Program record
Severity
High
CVSS
7.7 (3.1)
Known Exploited
No
Published

Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N

Official CVE source material

CNA and ADP enrichment extracted from CVE v5

These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.

1CVSS vectors
0Timeline events
0ADP providers
5Source links

CVSS vector scores

1 official score

We collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.

ScoreVersionSeverityVectorExploitImpactSource
7.7CVSS 3.1HighCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N3.14Primary CVE score

Vulnerability scoring details

Base CVSS 3.1 score

7.7High
CVSS 3.1 vector shape for CVE-2026-23529Attack VectorAttack ComplexityPrivileges RequiredUser InteractionScopeConfidentiality ImpactIntegrity ImpactAvailability Impact

Vector: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N

Attack Vector
NetworkAdjacentLocalPhysical
Attack Complexity
LowHigh
Privileges Required
NoneLowHigh
User Interaction
NoneRequired
Scope
ChangedUnchanged
Confidentiality Impact
HighLowNone
Integrity Impact
HighLowNone
Availability Impact
HighLowNone
Affected products

Products and packages named in the record

VendorProductVersion / packageStatus
Aiven-Openbigquery-connector-for-apache-kafka< 2.11.0Listed
Weakness

CWE details

CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.

CWE-73 · source CWE mapping

External Control of File Name or Path

External Control of File Name or Path represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.

CWE-918 · source CWE mapping

Server-Side Request Forgery (SSRF)

Server-Side Request Forgery (SSRF) represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.