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nginx-ui has Race Condition that Leads to Persistent Data Corruption and Service Collapse

High severity GitHub Reviewed Published Mar 28, 2026 in 0xJacky/nginx-ui • Updated Mar 30, 2026

Package

gomod github.com/0xJacky/Nginx-UI (Go)

Affected versions

<= 1.99

Patched versions

None
gomod github.com/uozi-tech/cosy (Go)
<= 1.30.0
1.30.1

Description

Summary

The nginx-ui application is vulnerable to a Race Condition. Due to the complete absence of synchronization mechanisms (Mutex) and non-atomic file writes, concurrent requests lead to the severe corruption of the primary configuration file (app.ini). This vulnerability results in a persistent Denial of Service (DoS) and introduces a non-deterministic path for Remote Code Execution (RCE) through configuration cross-contamination.

Details

The vulnerability exists because the settings update pipeline does not implement any synchronization primitives. When multiple requests reach the handler simultaneously:

  1. Memory Corruption: ProtectedFill() modifies shared global singleton pointers without thread-safety, leading to inconsistent states in memory.
  2. File Corruption: The underlying library (gopkg.in/ini.v1) performs direct overwrites. Concurrent write operations interleave at the OS level, resulting in app.ini files with empty leading lines, truncated fields, or partially overwritten configuration keys.
  3. State Persistent Failure: Depending on which bytes are corrupted, the application either fails its "is-installed" check (redirecting to /install) or encounters a fatal error during boot/runtime that prevents the process from responding to any further requests.

Environment:

  • OS: Kali Linux 6.17.10-1kali1 (6.17.10+kali-amd64)
  • Application Version: nginx-ui v2.3.3 (513) e5da6dd (go1.26.0)
  • Deployment: Docker Container

PoC

  1. Check original app.ini file valid state:

image

  1. Log in to the nginx-ui dashboard.
  2. Navigate to Preferences and update settings. Capture a POST /api/settings request and send it to Burp Suite Intruder.
  3. Configure the attack with Null payloads (to test basic concurrency) or a Fuzzing list (to test data-driven corruption).
  4. Set the Resource Pool to 20-50 concurrent requests.

image

  1. Observation (In-flight corruption): Monitor the app.ini file. You will observe the file being written with empty leading lines or incomplete key-value pairs.
  • image
  • image
  1. Observation (Recovery Failure): If the service redirects to /install, attempting to complete the setup again often fails because the underlying configuration state is too corrupted to be reconciled by the installer logic.
  2. Observation (Total Service Collapse): When the corruption in app.ini becomes so severe, the Go runtime or the INI parser encounters a fatal error, causing the Nginx-UI service to stop responding entirely (Hard DoS).

image

  1. Observation (Cross-Section Contamination): During testing, it was observed that sometimes INI sections become interleaved. For example, fields belonging to the [nginx] section (like ConfigDir or ReloadCmd) were erroneously written under the [webauthn] section.

    Example of corrupted output observed:

[webauthn]
RPDisplayName  = 
RPID           = 
RPOrigins      = 
gDirWhiteList  = 
ConfigDir      = /etc/nginx
ConfigPath     = 
PIDPath        = /run/nginx.pid
SbinPath       = 
TestConfigCmd  = 
ReloadCmd      = nginx -s reload
RestartCmd     = nginx -s stop
StubStatusPort = 51820
ContainerName  =

Impact

This is a High security risk (CWE-362: Race Condition).

  • Integrity: Permanent corruption of application settings and system-level configuration.
  • Availability: High. The attack results in a persistent Denial of Service that cannot be recovered via the web UI.
  • Remote Code Execution (RCE) Risk: Since the application allows updating certain fields (like Node Name) and uses others as shell commands (like ReloadCmd or RestartCmd), the observed "cross-contamination" of INI values means an attacker could potentially force a user-controlled string into a command execution field. If ReloadCmd is overwritten with a malicious payload provided in another field, the next nginx reload will execute that payload. While highly impactful, this specific exploit path is non-deterministic and depends on the precise interleaving of thread execution, making targeted exploitation difficult.

Recommended Mitigation

  1. Implement Mutex Locking: Wrap the ProtectedFill and settings.Save() calls in a sync.Mutex to serialize access to global settings.
  2. Atomic File Writes: Implement a "write-then-rename" strategy. Write the new configuration to app.ini.tmp and use os.Rename() to replace the original file atomically, ensuring the configuration file is always in a valid state.

A patched version of nginx-ui is available at https://github.com/0xJacky/nginx-ui/releases/tag/v2.3.4.

References

@0xJacky 0xJacky published to 0xJacky/nginx-ui Mar 28, 2026
Published to the GitHub Advisory Database Mar 30, 2026
Reviewed Mar 30, 2026
Published by the National Vulnerability Database Mar 30, 2026
Last updated Mar 30, 2026

Severity

High

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 Low
Attack Requirements None
Privileges Required High
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity High
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:L/AT:N/PR:H/UI:N/VC:L/VI:H/VA:H/SC:N/SI:N/SA:N

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.
(24th percentile)

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-2026-33028

GHSA ID

GHSA-m468-xcm6-fxg4

Source code

Credits

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