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Introduction:
The intersection of AI-powered development tools and cloud security has been thrown into sharp relief by a recently disclosed high-severity vulnerability in Amazon Q Developer. Discovered by Wiz Research and tracked as CVE-2026-12957 and CVE-2026-12958, the flaw allowed attackers to achieve arbitrary code execution and cloud credential theft simply by tricking a developer into opening a malicious code repository. This incident underscores a critical and growing systemic risk: the automatic execution of untrusted configuration files by AI coding assistants, which can turn a developer’s IDE into a launchpad for large-scale cloud account compromise.
Learning Objectives:
- Understand the technical root cause of CVE-2026-12957 and CVE-2026-12958 in Amazon Q Developer.
- Learn how attackers can exploit MCP server auto-execution to steal cloud credentials and environment variables.
- Identify affected products and versions, and implement the necessary remediation steps.
- Recognize broader industry patterns of similar vulnerabilities in AI coding tools.
- Apply practical hardening measures to secure development environments against such supply chain and trust-boundary attacks.
You Should Know:
- The MCP Auto-Execution Flaw: How Amazon Q Became an Attack Vector
The vulnerability stemmed from two critical behaviors in how Amazon Q Developer handled Model Context Protocol (MCP) server configurations. MCP is a standard that allows AI assistants to spawn local processes called “MCP servers” to extend their capabilities—connecting to databases, calling APIs, or accessing local resources. The security model for MCP assumes that users explicitly configure these servers, thereby granting informed consent.
However, Amazon Q violated this assumption in two ways:
Problem 1: Auto-execution Without Consent – The extension automatically loaded and executed `.amazonq/mcp.json` from the workspace root immediately upon opening a folder. No dialog asked the user to approve these MCP servers, and no workspace trust check prevented execution in untrusted folders.
Problem 2: Full Environment Inheritance – Spawned processes inherited the user’s complete environment, including AWS credentials (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN), cloud CLI authentication tokens, API keys, and SSH agent sockets.
The combination meant that a single malicious configuration file could execute arbitrary commands with full access to the developer’s credentials—no user interaction required beyond opening the folder and activating Amazon Q.
Proof of Concept (PoC): Wiz researchers demonstrated that a malicious `.amazonq/mcp.json` file could run `aws sts get-caller-identity` and exfiltrate the output to an attacker-controlled server. This command returns the developer’s AWS account ID, user ARN, and session credentials—everything an attacker needs to access cloud resources.
2. Affected Products, Versions, and Attack Scenarios
AWS has confirmed that the following products and versions are affected:
- Language Servers for AWS: < 1.69.0
- Amazon Q Developer for Visual Studio Code: < 2.20
- Amazon Q Developer for JetBrains: < 4.3
- Amazon Q Developer for Eclipse: < 2.7.4
- AWS Toolkit with Amazon Q for Visual Studio: < 1.94.0.0
Attack Scenarios: Beyond opportunistic exploitation, researchers highlighted several targeted attack vectors:
- Malicious pull requests to popular open-source repositories.
- Typosquatted packages embedding hidden `.amazonq/` configurations.
- Fake job interview coding tests—a tactic used by DPRK-linked threat actors—where candidates are asked to clone and run attacker-controlled repositories.
3. Remediation: Patching and Verification
AWS has remediated both issues in Language Servers for AWS version 1.69.0. The language server updates automatically for most users unless network configuration prevents it.
Step-by-Step Remediation Guide:
For most users (auto-update enabled):
- Close and reload your IDE (VS Code, JetBrains, Eclipse, or Visual Studio).
- This triggers an update to the latest language server version (1.69.0 or later).
For users with auto-update blocked:
- Manually upgrade to the latest version of your Amazon Q Developer IDE plugin.
- For VS Code: Update the extension via the Extensions panel or run:
code --install-extension amazon-q-developer --force
- For JetBrains: Check for updates via the Plugins marketplace.
- For Eclipse and Visual Studio: Download and install the latest plugin versions from the respective marketplaces.
Verification Commands:
To confirm you are running a patched version:
- VS Code: Check the extension version in the Extensions panel. Ensure it is ≥ 2.20.
- Language Server: The fix is included in Language Servers for AWS version 1.69.0.
- AWS CLI verification: After updating, you can verify your environment is secure by running:
aws sts get-caller-identity
This should return your identity without any unexpected exfiltration attempts.
4. The Broader Industry Pattern: A Systemic Risk
Wiz noted that the underlying issue is not unique to Amazon Q. Similar problems have been identified in other AI coding tools, including Claude Code (CVE-2025-59536, CVE-2026-21852), Cursor, and Codeium’s Windsurf (CVE-2026-30615). OX Security and Check Point Research independently discovered similar MCP auto-execution vulnerabilities around the same time.
This pattern reveals a systemic risk: MCP, by design, gives AI assistants the ability to call external tools with whatever permissions the host application holds. When a repository can silently register an MCP server that inherits a developer’s cloud credentials, the attack surface expands from the code itself to every service the developer can access.
5. Hardening Your Development Environment
Given the growing threat landscape, developers and security teams should adopt the following hardening measures:
For Developers:
- Treat unfamiliar repositories as untrusted: Avoid opening repositories from unverified sources.
- Inspect `.amazonq/` directories in cloned repositories for unexpected MCP configurations.
- Review consent prompts: Amazon Q now displays “Untrusted MCP Server” prompts before approving execution. Always review these carefully.
- Limit environment variables: Consider using tools like `direnv` or `.env` files to limit the scope of environment variables exposed to IDE plugins.
- Use IAM roles with least privilege: Avoid using root or overly permissive IAM credentials in development environments.
For Security Teams:
- Monitor for suspicious MCP server activity: Look for unexpected processes spawned by IDE extensions.
- Implement network controls: Block outbound connections from developer workstations to unknown external IPs.
- Conduct regular audits: Review recently cloned repositories for unexpected configuration files.
- Educate developers: Raise awareness about supply chain risks and the dangers of auto-executing configurations.
- Linux and Windows Commands for Detection and Mitigation
Linux/macOS:
Check for suspicious .amazonq directories in recent clones
find ~/projects -type d -1ame ".amazonq" -exec ls -la {} \;
Monitor for unexpected MCP server processes
ps aux | grep -i mcp
Audit environment variables in your IDE session
env | grep -E "AWS_|AZURE_|GOOGLE_"
Use inotify to monitor for new .amazonq files (real-time detection)
inotifywait -m -r ~/projects -e create -e modify --format '%w%f' | grep -i ".amazonq"
Windows (PowerShell):
Search for .amazonq directories
Get-ChildItem -Path C:\Users\$env:USERNAME\projects -Directory -Recurse -Filter ".amazonq"
Check environment variables
Get-ChildItem Env: | Where-Object { $<em>.Name -match "AWS</em>|AZURE_|GOOGLE_" }
Monitor for new .amazonq files (using FileSystemWatcher)
$watcher = New-Object System.IO.FileSystemWatcher
$watcher.Path = "C:\Users\$env:USERNAME\projects"
$watcher.Filter = "."
$watcher.IncludeSubdirectories = $true
$watcher.EnableRaisingEvents = $true
Register-ObjectEvent $watcher "Created" -Action { if ($Event.SourceEventArgs.Name -match ".amazonq") { Write-Host "Suspicious file detected: $($Event.SourceEventArgs.FullPath)" } }
7. API Security and Cloud Hardening Considerations
This vulnerability highlights the critical importance of API security and cloud hardening:
- Credential Rotation: Regularly rotate AWS access keys and use temporary credentials (STS) where possible.
- IAM Policy Hardening: Implement strict IAM policies that limit what actions can be performed from development environments.
- VPC Endpoints: Use VPC endpoints for AWS services to prevent credentials from being exfiltrated to the public internet.
- CloudTrail Monitoring: Enable AWS CloudTrail and set up alerts for unusual API calls, especially from unexpected IP addresses.
- Secrets Management: Use AWS Secrets Manager or Parameter Store to manage secrets, rather than hardcoding them in environment variables.
What Undercode Say:
- Key Takeaway 1: The Amazon Q vulnerability is a wake-up call for the AI coding assistant ecosystem. Auto-execution of untrusted configurations without user consent is a fundamental design flaw that must be addressed industry-wide. The fact that similar vulnerabilities exist in Claude Code, Cursor, and Windsurf suggests this is not an isolated incident but a systemic problem.
-
Key Takeaway 2: Developers and security teams must adopt a zero-trust approach to development environments. Opening a repository should never be treated as a safe operation, especially when AI tools are involved. The attack surface has expanded from code review to configuration files that can execute arbitrary commands with full cloud credentials.
Analysis: The timeline of this vulnerability is particularly telling. Wiz Research discovered the flaw on April 20, 2026, and AWS deployed a fix on May 12, with public disclosure on June 26. This two-month window between patch and disclosure is standard for responsible disclosure, but it also means that many developers may have been vulnerable for weeks without knowing it. The fact that CISA’s advisory database lists no known attacks is reassuring, but the potential for exploitation was significant. The vulnerability required no user interaction beyond opening a folder—a routine action for any developer. This makes it an ideal vector for supply chain attacks, where malicious actors could compromise popular repositories or use typosquatting to distribute malicious configurations at scale. The broader lesson is clear: as AI tools become more powerful and deeply integrated into development workflows, the trust boundaries between code, configuration, and execution must be rigorously enforced.
Prediction:
- +1 The disclosure of these vulnerabilities will accelerate the adoption of stricter security standards for AI coding assistants, including mandatory user consent for any configuration-driven code execution.
- +1 IDE vendors will likely implement workspace trust features more prominently, similar to VS Code’s existing Workspace Trust model, but with additional safeguards for AI-specific configurations.
- -1 Attackers will increasingly target AI coding assistants as a high-value entry point into cloud environments, given the elevated privileges these tools often hold.
- -1 The frequency of similar vulnerabilities may increase as more AI tools adopt MCP and similar protocols without adequate security reviews.
- +1 Organizations will invest more in developer security training and automated scanning of repositories for suspicious configuration files, reducing the overall risk profile.
- -1 The complexity of securing AI development tools will grow, requiring continuous monitoring and rapid patch cycles that many organizations may struggle to maintain.
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