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Juju affected by Confused Deputy IDOR attack via Predictable user specified ID in Juju Secrets

Moderate severity GitHub Reviewed Published Mar 18, 2026 in juju/juju • Updated Mar 19, 2026

Package

gomod github.com/juju/juju (Go)

Affected versions

>= 0.0.0-20221021155847-35c560704ee2, < 0.0.0-20260319091847-d06919eb03ec

Patched versions

0.0.0-20260319091847-d06919eb03ec

Description

Summary

Predictable secret ID and lack of secret origin API enable confused deputy attacks on Juju workloads.

Details

A Juju application can create a secret and grant it to another integrated application (grantee).

When they do so, the secret owner has to communicate the secret id to the grantee.

The grantee, having received the secret id can load the secret content and perform operations on behalf of the secret owner.

However, today the grantee has no way to determine which granted secret belongs to which owner.

Instead the grantee relies on:

  • being able to read the secret by id (secret was in fact granted, by some entity)
  • secret id was received over a relation (the remote end of the relation is presumed to be secret owner)

Additionally, secret IDs are XID, which are predictable, here two secrets created by two distinct apps in the same K8s model close in time:

d34vsl7mp25c76301hs0
time (UTC): 2025-09-17 00:18:28 (Unix 1758068308)
machine: f6c88a
pid: 50072
counter: 6294648

d34vslfmp25c76301hsg
time (UTC): 2025-09-17 00:18:29 (Unix 1758068309)
machine: f6c88a
pid: 50072
counter: 6294649

PoC

This allows for an IDOR attack where:

  • actors:
    • a Good application (the owner of the Victim),
    • an Evil application, and
    • a Provider application (the Confused Deputy)
  • relations: Good --- Provider, Evil --- Provider
  • secrets: Good and Evil create Secrets, granting them to the Provider and communicate Secret IDs with the Provider.
  • semantics: the Provider performs some operation on behalf of the Good/Evil using the Secret.
  • weakness 1: Evil can guess the Secret ID that Good granted and communicated to Provider.
  • weakness 2: Juju doesn't provide the Provider application the facility to verify the provenance of the Secret IDs.
  • exploit: Evil passes Good's secret id to Provider.
  • bypass: Provider performs evil operation with Good's Secret ID on behalf of Evil.

Evil could benefit by:

  • exfiltrating Good's Secret via reflection.
  • reading or mutating Good's resources accessible via *Good's Secret.

Impact

This requires a complex setup.

Not all shared secrets are used like above, so an actual exploit requires a very specific relation interface, specific semantics of the data in the databag, and an administrator having a reasonable need to deploy two apps (one evil, one good) related to the same (third) provider app.

If exploited, it can be very hard to determine what went wrong after the fact.

Suggested remediation

1. Longer, random secret IDs

For example, if the secret id was extended with a 128-bit nonce, guessing a sibling secret ID would be infeasible, and an attack of this style would require another weakness (e.g. secret IDs exposed in logs)

2. Grantee secret API

Today, an app is not allowed to call secret-info-get on the granted secret.
Additionally, granted secrets are not included in the secret-ids output.

Suppose that the Provider could run these hook tools:

(provider/0)> secret-ids
my-own-secret-123

(provider/0)> secret-ids --grants
good-secret-id-42
evil-secret-id-43

(provider/0)> secret-info-get good-secret-id-42
good-secret-id-42:
  revision: 1
  label: ""
  owner: good
  grant-relation-id: 12
  rotation: never

The Provider would then able to validate the secret ID it's about to use against:

  • the relation in which the secret ID has been passed (good relation 12 or evil relation 14)
  • the application or unit name of the secret owner (good or evil)

References

@korhlibri korhlibri published to juju/juju Mar 18, 2026
Published by the National Vulnerability Database Mar 18, 2026
Published to the GitHub Advisory Database Mar 19, 2026
Reviewed Mar 19, 2026
Last updated Mar 19, 2026

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
High
Privileges required
High
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(12th percentile)

Weaknesses

Predictable Value Range from Previous Values

The product's random number generator produces a series of values which, when observed, can be used to infer a relatively small range of possibilities for the next value that could be generated. Learn more on MITRE.

CVE ID

CVE-2026-32694

GHSA ID

GHSA-5cj2-rqqf-hx9p

Source code

Credits

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