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Juju: In-Memory Token Store for Discharge Tokens Lacks Concurrency Safety and Persistence

Moderate severity GitHub Reviewed Published Apr 10, 2026 in juju/juju • Updated Apr 10, 2026

Package

gomod github.com/juju/juju (Go)

Affected versions

< 0.0.0-20260408003526-d395054dc2c3

Patched versions

0.0.0-20260408003526-d395054dc2c3

Description

Summary

The localLoginHandlers struct in the Juju API server maintains an in-memory map to store discharge tokens following successful local authentication. This map is accessed concurrently from multiple HTTP handler goroutines without any synchronization primitive protecting it. The absence of a mutex or equivalent mechanism means that concurrent reads, writes, and deletes on the map can trigger Go runtime panics and may allow a discharge token to be consumed more than once before deletion completes.

Details

When a user authenticates through the local login flow, a discharge token is generated and stored in a plain map[string]string field named userTokens. The form handler writes to this map when authentication succeeds, and the third-party caveat checker reads from and deletes from the same map when a discharge request arrives. Both code paths execute inside goroutines dispatched by the HTTP server, meaning concurrent requests will access the map simultaneously.

Go's runtime detects concurrent map access and will terminate the process with a fatal error when a write races with another write or read. This makes the API server susceptible to a denial-of-service attack from any authenticated user who can trigger simultaneous discharge requests. Beyond the crash scenario, the read-then-delete sequence in the caveat checker is not atomic. Two goroutines processing the same token concurrently may both pass the existence check before either executes the deletion, allowing a single-use discharge token to be accepted more than once and effectively replaying authentication.

The struct definition that introduces the unsafe field is shown below.

type localLoginHandlers struct {
    authCtxt   *authContext
    userTokens map[string]string
}

The concurrent access originates from the caveat checker calling username, ok := h.userTokens[tokenString] followed by delete(h.userTokens, tokenString) with no lock held, while formHandler concurrently executes h.userTokens[token] = username in a separate goroutine.

PoC

package main

import (
    "net/http"
    "sync"
)

func main() {
    token := "acquired-discharge-token"
    endpoint := "https://target-juju-api:17070/local-login/discharge"

    var wg sync.WaitGroup
    for i := 0; i < 20; i++ {
        wg.Add(1)
        go func() {
            defer wg.Done()
            req, _ := http.NewRequest("GET", endpoint+"?token="+token, nil)
            http.DefaultClient.Do(req)
        }()
    }
    wg.Wait()
}

Impact

Any authenticated user who obtains a valid discharge token can send a burst of concurrent requests to the discharge endpoint. The most reliable outcome is a Go runtime panic caused by concurrent map access, which terminates the Juju API server process and denies service to all connected clients and agents. Under favorable timing conditions the same token may be accepted by multiple goroutines before deletion, bypassing the single-use enforcement and allowing repeated authentication with a token that should have been invalidated after first use.

References

@Fedqys Fedqys published to juju/juju Apr 10, 2026
Published by the National Vulnerability Database Apr 10, 2026
Published to the GitHub Advisory Database Apr 10, 2026
Reviewed Apr 10, 2026
Last updated Apr 10, 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 v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity High
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity Low
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:H/AT:P/PR:L/UI:N/VC:L/VI:L/VA:H/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')

The product contains a concurrent code sequence that requires temporary, exclusive access to a shared resource, but a timing window exists in which the shared resource can be modified by another code sequence operating concurrently. Learn more on MITRE.

CVE ID

CVE-2026-5774

GHSA ID

GHSA-7m55-2hr4-pw78

Source code

Credits

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