CVE-2026-115886VulnerabilityPublished 29 Oct 2026

MLflow: SSRF on unauthenticated MLflow servers via third-party scorer kwargs in the scorer invoke, register, and GenAI

Affects mlflowSource GCVE Database

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Authoritative record:CVE-2026-115886· Medium 6.5

Not known to be exploited · public detection template (Nuclei) · CVSS 6.5 Medium : upgrade to 3.17.0 when convenient.

Data as of 29 Oct 2026, 14:41 UTC

CVSS 3.1 base score

6.5Medium

How severe the flaw is on the 0–10 CVSS scale.

Thin evidence

One scorer or none

CVSS scores by source
CNA (GitHub_M)	CVSS 3.1	6.5

EPSS: 0.6% chance of exploitation in 30 days – higher than 52% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 3.17.0

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

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: Low
Integrity: Low
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 23 Oct 2026
Detectable: evidence found.
nuclei template: MLflow <3.17.0 - Unauthenticated SSRF via Third-Party (TruLens) Scorer
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade mlflow to 3.17.0.

Affected software

Product	Affected	Fixed in
Bitnamimlflow`pkg:bitnami/mlflow`Other threats	Affected >=3.12.0 <3.17.0	Fixed in 3.17.0

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Upgrade MLflow to version 3.17.0 or later, where this vulnerability is fixed. Since a patch is available and the issue is resolved in the fixed version, applying the official update is the recommended mitigation. No additional vendor advisories indicate alternative mitigations or that no action is required.

Description

MLflow versions from 3.12.0 up to but not including 3.17.0 contain a server-side request forgery (SSRF) vulnerability in the scorer invoke, register, and GenAI evaluate endpoints. This vulnerability allows unauthenticated attackers to send crafted requests that cause the server to make outbound HTTP requests to attacker-controlled or internal hosts. The issue arises from insecure deserialization of third-party scorer data that is resolved using a module-path allowlist but does not restrict constructor arguments. The vulnerability is fixed in version 3.17.0.

Impact

An unauthenticated attacker can exploit this vulnerability to cause the MLflow server to make arbitrary outbound HTTP requests to attacker-chosen or internal hosts. This can lead to information disclosure, internal network scanning, or interaction with internal services not normally accessible externally. The impact is limited to SSRF and does not include confirmed remote code execution or data corruption. No known exploits in the wild have been reported.

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 29 Oct 2026, 13:35 UTC

Public exploits and detectiona Nuclei detection template

Technical details

References

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