Listen to this Post
Introduction:
Anthropic’s Code, an AI‑powered coding assistant, recently suffered a catastrophic source‑code leak of over 500,000 lines across 1,900 files—exposing not only proprietary secrets but also a cascade of critical security vulnerabilities. The incident, traced to a manual deployment step that “should have been better automated,” was followed by the discovery of multiple high‑severity flaws, including command injection (CVE‑2025‑66032, CVSS 9.8), denial‑of‑service via prompt injection, and exposure of environment variables, turning a trusted developer tool into a potential backdoor for remote code execution (RCE) and API credential theft. This article dissects the technical root causes, provides hands‑on remediation commands, and outlines how to audit and harden AI coding assistants in your DevOps pipeline.
Learning Objectives:
- Understand the cascade of security failures—from the source‑code leak to RCE vulnerabilities—in AI‑powered coding assistants.
- Apply Linux/Windows commands and configuration changes to patch, sandbox, and monitor Code and similar MCP‑based tools.
- Implement proactive security measures, including input validation, permission controls, and environment‑variable redaction, to prevent exploitation in CI/CD and local development environments.
You Should Know:
- Patch & Harden Code Against RCE and Prompt Injection
The leaked code and subsequent audits revealed several critical vulnerabilities that can be triggered via malicious repositories or crafted inputs. Below are the actionable steps to verify your version, apply patches, and add defense‑in‑depth controls.
Step‑by‑Step Guide:
- Check your current Code version and update to the latest secure release (≥1.0.93 for CVE‑2025‑66032, ≥1.0.105 for the git config RCE, ≥2.1.90 for the deny‑rule bypass):
Linux / macOS / WSL --version npm update -g @anthropic-ai/-code --version Confirm update
Windows (PowerShell) --version npm update -g @anthropic-ai/-code --version
- Enable automatic updates to receive security patches without delay:
Set auto‑update in Code settings config set autoUpdate true
- Strengthen deny rules to block dangerous commands even when the agent faces long subcommand chains (the `MAX_SUBCOMMANDS_FOR_SECURITY_CHECK` cap was a key weakness). Edit `~/./settings.json` (Linux/macOS) or `%USERPROFILE%\.\settings.json` (Windows):
{
"deny": ["Bash(curl:)", "Bash(wget:)", "Bash(nc:)", "Bash(eval:)", "Bash(exec:)"],
"permissions": {
"defaultMode": "ask",
"additionalDirectories": []
}
}
- Implement environment‑variable redaction to prevent from echoing sensitive tokens (e.g.,
GH_TOKEN,API_KEY). Use a pre‑tool‑use hook that scans and sanitises commands:
Create a hook script (Linux/macOS) cat > ~/./hooks/pre-tool-use.sh << 'EOF' !/bin/bash Block commands that try to echo or display known sensitive environment variables if echo "$1" | grep -E "echo\s+\$?(GH_TOKEN|API_KEY|AWS_SECRET|DB_PASSWORD)"; then echo "BLOCKED: Attempt to display sensitive environment variable" exit 1 fi EOF chmod +x ~/./hooks/pre-tool-use.sh
Then register the hook in `~/./settings.json`:
{
"hooks": {
"preToolUse": "~/./hooks/pre-tool-use.sh"
}
}
2. Audit Malicious Repositories and CI/CD Pipelines
Attackers can embed malicious configuration files in shared repositories. When Code loads a project, it automatically executes these files, leading to RCE or credential exfiltration before the user confirms trust. The following steps help you detect and block such threats.
Step‑by‑Step Guide:
- Scan for suspicious project‑level config files that may contain injected commands. Pay special attention to
./settings.json,CLAUDE.md, and any `.env` files.
Linux/macOS – find and inspect config files recursively
find . -type f ( -name "CLAUDE.md" -o -name "settings.json" -o -name ".env" ) -exec cat {} \;
Windows PowerShell – recursively find and display config files
Get-ChildItem -Recurse -Include "CLAUDE.md", "settings.json", ".env" | ForEach-Object { "`n $($<em>.FullName) "; Get-Content $</em>.FullName }
- Use `gitleaks` or `truffleHog` to detect hard‑coded secrets that may have been accidentally exposed or planted:
Install and run gitleaks (Linux/macOS/WSL) docker run --rm -v $(pwd):/path zricethezav/gitleaks:latest detect --source="/path" --verbose
- Run Code in a sandboxed environment for untrusted projects. Use Docker to limit network and filesystem access:
Run Code inside a read‑only container with no network access docker run --rm -it -v $(pwd):/workspace:ro --network none anthropic/-code:latest
- In CI/CD pipelines, avoid using `–dangerously‑skip‑permissions` and instead run Code in non‑interactive mode with explicit approval rules. Example for GitHub Actions:
- name: Run Code with explicit allow list run: | "review this PR" --allowed-tools "Read,Edit" --max-iterations 5 env: CLAUDE_CODE_PERMISSION_MODE: "non-interactive"
3. Harden AWS Bedrock Integration and IAM Policies
Many organisations use Code with Amazon Bedrock. Misconfigured IAM roles or overly permissive policies can amplify the impact of a compromised agent. The steps below restrict Code’s access to the bare minimum.
Step‑by‑Step Guide:
- Verify your Code‑to‑Bedrock configuration and ensure it uses a dedicated IAM role with least privilege. Use the `-bedrock-setup` tool to audit current settings:
Install the audit tool pip install -bedrock-setup Check current configuration -bedrock-setup status Reset to safe defaults -bedrock-setup reset
- Apply a restrictive IAM policy that only allows the necessary Bedrock actions. Replace the generic `”bedrock:”` with explicit permissions:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"bedrock:InvokeModel",
"bedrock:ListFoundationModels"
],
"Resource": "arn:aws:bedrock:::foundation-model/anthropic.-"
}
]
}
- Enable AWS CloudTrail logging for Bedrock API calls to detect anomalous invocations:
aws cloudtrail create-trail --name -code-audit --s3-bucket-name your-bucket aws cloudtrail start-logging --name -code-audit
- Monitor for suspicious command execution using AWS GuardDuty or a custom Lambda that parses CloudTrail logs for unexpected `InvokeModel` patterns.
- Detect & Mitigate Prompt Injection via Tool Poisoning
A recent empirical study on MCP clients found that Code is vulnerable to cross‑tool poisoning and hidden parameter exploitation. Attackers can embed prompts in seemingly harmless files (e.g., a README.md) that trick the agent into revealing secrets or executing commands.
Step‑by‑Step Guide:
- Use static validation to scan incoming files for known injection patterns. The following command detects suspicious markers in markdown and config files:
Linux/macOS – search for potential injection syntax
grep -rnE '(system\s:|user\s:|assistant\s:|<|||>|<code>.</code>.\$(|\$(.)|{{.}})' --include=".md" --include=".json" --include=".yaml" .
- Implement a pre‑tool‑use hook that logs and blocks unusual tool sequences. For example, block any command that tries to read `/etc/passwd` or
~/.aws/credentials:
Extended hook script (Linux/macOS) cat > ~/./hooks/pre-tool-use.sh << 'EOF' !/bin/bash COMMAND="$1" if echo "$COMMAND" | grep -qE '(cat|head|tail|less|more)\s+/etc/passwd'; then echo "BLOCKED: Attempt to read /etc/passwd" exit 1 fi if echo "$COMMAND" | grep -qE '(cat|head|tail|less|more)\s+..aws/credentials'; then echo "BLOCKED: Attempt to read AWS credentials" exit 1 fi exit 0 EOF chmod +x ~/./hooks/pre-tool-use.sh
- Enable audit logging in Code to record all tool invocations. Redirect logs to a central SIEM:
Start Code with verbose logging --log-level debug --log-file ~/./audit.log Forward logs to syslog (Linux) tail -f ~/./audit.log | logger -t -code
5. Windows‑Specific Hardening for Code
Windows environments face additional risks due to PowerShell’s extensive system access. The following commands restrict Code’s execution context on Windows.
Step‑by‑Step Guide:
- Run Code under a constrained user account with limited privileges. Use `RunAs` or create a dedicated local user:
Create a restricted user (PowerShell as Admin) New-LocalUser -Name "Limited" -Password (ConvertTo-SecureString "TempP@ss123!" -AsPlainText -Force) -AccountNeverExpires Run Code as that user runas /user:Limited " --help"
- Use Windows Defender Application Control (WDAC) to whitelist only the Code binary and its allowed child processes:
Generate a WDAC policy (PowerShell as Admin) New-CIPolicy -Level Publisher -FilePath "C:\WDAC\Code.xml" Merge the policy with the base policy Merge-CIPolicy -PolicyPaths "C:\WDAC\Code.xml" -OutputFilePath "C:\WDAC\MergedPolicy.xml" Activate the policy Set-CIPolicy -FilePath "C:\WDAC\MergedPolicy.xml"
- Block Code from accessing sensitive registry keys using AppLocker or a custom PowerShell Constrained Language Mode:
Set PowerShell to Constrained Language Mode for Code's process $ps = Start-Process -NoNewWindow -PassThru -FilePath "powershell.exe" -ArgumentList "-NoProfile -Command `$ExecutionContext.SessionState.LanguageMode = 'ConstrainedLanguage'; --help"
6. Hardening MCP Clients Beyond Code
The same vulnerabilities (tool poisoning, hidden parameters) affect other MCP clients such as Cursor, Cline, and Continue. Apply similar controls across your toolchain.
Step‑by‑Step Guide:
- For Cursor, disable automatic execution of MCP tools and require manual approval:
// In ~/.cursor/settings.json
{
"mcp.autoApproveTools": false,
"mcp.toolTimeoutSeconds": 30
}
- For Cline (VS Code extension) , restrict file system access using VS Code’s workspace trust settings:
Set workspace trust to "restricted" for all new folders code --set-config "security.workspace.trust.enabled" true
- Audit all MCP servers in your environment. List running servers and their permissions:
Linux – find MCP server processes ps aux | grep -E "mcp-server|-desktop|cursor" Check network connections initiated by MCP tools sudo netstat -tunap | grep -E "|cursor|cline"
What Undercode Say:
- Trust no input, not even from your AI assistant. The Code leak proved that “secure by design” is meaningless when manual deployment steps bypass automation and expose source code. Every AI coding tool must be treated as a potential attack vector.
- Vulnerabilities in agentic tools are not theoretical. With CVE‑2025‑66032 scoring 9.8 on CVSS, an attacker can achieve RCE simply by adding untrusted content to the context window. If your organisation uses Code or similar MCP clients, you are already in the blast radius of a supply‑chain attack.
Prediction:
The Code breach and its aftermath mark a turning point for AI‑assisted development. Within 12 months, we will see regulatory mandates requiring source‑code escrow and third‑party security audits for all AI agents used in critical infrastructure. Organisations that fail to treat AI assistants as privileged, untrusted components will become the next headline—not for productivity gains, but for catastrophic data leaks and RCE incidents.
▶️ Related Video (78% Match):
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Matthewjohansen Boris – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
