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CVE Record

CVE-2026-4035: Environment Variable Resolution Vulnerability in mlflow/mlflow

A vulnerability in mlflow/mlflow versions prior to 3.11.0 allows for the resolution of environment variables in AI Gateway secrets, which can be exploited to exfiltrate sensitive server-side environment credentials to an attacker-controlled endpoint. This issue arises because the `api_key` field in gateway secrets can accept `$ENV_VAR` references, which are resolved against the MLflow server's environment during runtime. The resolved secrets are then sent in provider authentication headers to the configured upstream `api_base`. This vulnerability can be exploited by low-privileged authenticated users in basic-auth deployments or by unauthenticated users in default deployments without `basic-auth`. The impact includes potential leakage of sensitive credentials such as cloud artifact credentials (`AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`), which could lead to artifact poisoning and cross-boundary code execution in downstream environments. The issue is fixed in version 3.11.0.

CriticalCVSS 9.1Not KEV-listedUpdated
Glexia's TakeAutomated analysiscritical

Security readout for executives and security teams

Plain-English summary

MLflow before 3.11.0 can reveal secrets stored in its server environment. An attacker able to configure AI Gateway secrets may cause MLflow to resolve an environment-variable reference and send the resulting credential to an attacker-controlled service. Exposed cloud credentials could enable artifact tampering and potentially affect downstream systems.

Executive priority

Treat this as an immediate remediation item for exposed or shared MLflow services. Prioritize upgrading unauthenticated deployments and instances holding cloud or artifact credentials. If suspicious configuration or outbound traffic is found, begin credential rotation and investigate downstream artifact integrity.

Technical view

The AI Gateway accepted environment-variable references in the api_key field, resolved them against the MLflow server environment, and transmitted the resolved value in authentication headers to the configured api_base. Exposure requires no authentication in default deployments without basic-auth, or only low privileges when basic-auth is enabled. Version 3.11.0 fixes the issue.

Likely exposure

Internet- or broadly network-accessible MLflow deployments below 3.11.0 are most exposed, especially those using the AI Gateway and lacking basic-auth. Basic-auth reduces the attacker pool but remains vulnerable to low-privileged authenticated users. Impact depends on which credentials exist in the server environment and their permissions.

Exploitation context

The supplied record reports no CISA KEV listing and provides no evidence of active exploitation. Exploitation is nevertheless plausible because it requires low complexity, network access, and limited or no privileges depending on authentication configuration. The CVSS score is 9.1, with confidentiality as the primary impact.

Researcher notes

CWE-201 reflects unintended exposure of sensitive information. The described cross-boundary code-execution risk is indirect: leaked cloud credentials may permit artifact poisoning, which could later affect systems consuming those artifacts. The source bundle does not establish direct code execution through MLflow or exploitation in the wild.

Mitigation direction

  • Upgrade MLflow to version 3.11.0 or later.
  • Until upgraded, restrict AI Gateway configuration access to trusted administrators.
  • Constrain MLflow's outbound connections to approved provider endpoints where operationally feasible.
  • Rotate exposed or potentially exposed environment credentials and reduce their permissions.

Validation and detection

  • Confirm every MLflow instance reports version 3.11.0 or later.
  • Determine whether each deployment enables basic-auth and who can configure AI Gateway secrets.
  • Review gateway configurations for environment-variable references and unexpected api_base destinations.
  • Inspect relevant logs for suspicious gateway changes or outbound requests to unapproved endpoints.
  • Identify server environment credentials and assess whether rotation is required.
Prepared
Confidence
high
Sources
5

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

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cwe · medium confidence lookup

CWE-201: 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.

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description · low confidence lookup

Execution behavior lookup

The CVE wording references code or command execution, so execution technique review may help defensive triage. This is a Glexia inferred lookup path, not an official MITRE, ATT&CK, or CVE Program mapping.

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cve · low confidence lookup

CVE-2026-4035 mapping review

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Vulnerability profileCVE Program record
Severity
Critical
CVSS
9.1 (3.0)
Known Exploited
No
Published

Vector: CVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L

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.

2CVSS vectors
5Timeline events
2ADP providers
6Source links

SSVC decision data

CISA-ADPCISA Coordinator
Timestamp
Version
2.0.3
Exploitation: pocAutomatable: noTechnical Impact: partial

CVSS vector scores

2 official scores

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
9.1CVSS 3.0CriticalCVSS:3.0/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:L3.15.3@huntr_ai
7.7CVSS 3.1HighCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:N/A:N3.14redhat-SADP

Vulnerability scoring details

Base CVSS 3.1 score

7.7High
CVSS 3.1 vector shape for CVE-2026-4035Attack 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

Vulnerability timeline

Timeline events are normalized from CVE metadata, CNA source timelines, ADP timelines, and KEV metadata when present.

  1. CVE reservedCVE Program

    The CVE ID was reserved by the assigning CNA.

  2. ADP timelineredhat-SADP

    Made public.

  3. CVE publishedCVE Program

    The CVE record was published.

  4. ADP timelineredhat-SADP

    Reported to Red Hat.

  5. CVE updatedCVE Program

    The CVE record metadata indicates this as the latest update time.

ADP provider summaries

CISA-ADPCISA ADP Vulnrichment
other:ssvc
redhat-SADPpython-mlflow: MLflow: Sensitive credential exfiltration via environment variable resolution in AI Gateway secrets
other:Red Hat severity ratingcvssV3_1
  • 2026-06-03T09:00:55.993Z: Reported to Red Hat.
  • 2026-06-03T07:18:08.512Z: Made public.

Source materials

Affected products

Products and packages named in the record

VendorProductVersion / packageStatus
mlflowmlflow/mlflowunspecifiedListed
Weakness

CWE details

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

CWE-201 · source CWE mapping

Insertion of Sensitive Information Into Sent Data

Insertion of Sensitive Information Into Sent Data represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.