B — Some risk signals Graded October 16, 2026Minor concerns worth a quick check.Based on public adoption and transparency signals as of October 16, 2026. Our opinion, not a code audit or security guarantee.
AI agent skill · Developer tools
coderunner
A local sandbox for your AI agents
Bottom line: Signal-based grade (4/7 points): well starred on GitHub, listed in several sources, public source code. This reflects adoption and transparency, not a code audit.
- Popularity score
- 41/100
- Rank
- Not ranked: outside the 500 most popular tools
- GitHub stars
- 895
What it does
CodeRunner is a local sandbox environment that allows AI agents to safely execute code without exposing your main system. It isolates code execution in a containerized or virtual environment, enabling agents to run scripts, queries, and computations while maintaining security boundaries.
Who it’s for
Builders and executives deploying AI agents that need to execute dynamic code (data analysis, automation, tool use) while maintaining strict security and isolation. Teams concerned about prompt injection attacks or runaway code execution.
Copy-paste setup
Check these steps against the project’s own instructions before running anything.
Verify against the repo README at https://github.com/instavm/coderunner (opens external site). The project appears active but setup varies by integration pattern. Check https://github.com/instavm/coderunner/blob/main/SKILLS-README.md (opens external site) for agent skill configuration details.
Risks
- Sandbox escape vulnerabilities: Container/VM breakout could expose host system if CodeRunner has unpatched kernel or misconfigured isolation.
- Resource exhaustion: Malicious or poorly-written agent code could consume unbounded CPU, memory, or disk, causing denial-of-service.
- Data exfiltration via side-channels: Timing, power, or covert channels in sandbox could leak sensitive data despite isolation.
- Dependency supply-chain risk: CodeRunner and its transitive dependencies could be compromised; verify lock files and audit regularly.
- Credentials/secrets in agent prompts: If agent receives API keys or database URLs in context, they could be logged or exfiltrated by sandboxed code.
How to stay secure
Least-privilege permissions
- Run CodeRunner as a low-privilege user account without administrative access, so even if code breaks out, the damage is limited.
- Restrict file access to only the specific directories CodeRunner needs; block read/write access to sensitive system files and credential stores.
- Disable unnecessary system calls (use seccomp filters—rules that prevent code from calling dangerous operating system functions) to block sandbox-escape techniques.
- Use read-only container images where the base system cannot be modified, forcing any changes into temporary memory that disappears when CodeRunner stops.
Network isolation
- Block all outbound network access by default; only permit explicitly whitelisted external APIs that agents genuinely need.
- Isolate CodeRunner on a separate network segment (e.g., a dedicated subnet or VLAN) so if compromised, it cannot directly access databases or internal services.
- Disable local networking to the host machine to prevent agents from connecting to management interfaces or stealing credentials from other services running nearby.
Monitoring
- Log all code execution (script names, parameters, start/stop times, user who triggered it) to detect suspicious patterns or repeated failures.
- Set resource limits (CPU time, memory, disk space) and alert if any single run approaches them—a sign of runaway or hostile code.
- Track dependencies and patches: maintain a bill of materials for CodeRunner and all libraries it uses, and scan monthly for known vulnerabilities.
- Audit outbound connection attempts, even blocked ones, to catch agents trying to exfiltrate data or contact external servers.
Red flags to watch for
- Secrets appearing in agent prompts or logs (API keys, passwords, database URLs)—immediately rotate them and review access controls.
- CodeRunner consuming abnormal CPU or memory or creating large temporary files, especially if triggered by user input—likely resource exhaustion or cryptomining.
- Multiple failed sandbox operations or unusual system calls in logs—may indicate an escape attempt or malformed code.
- Unexpected outbound connection attempts or network timeouts—agents may be probing for external services or side-channel leaks.
Alternatives
- E2B Code Interpreter – Managed cloud sandbox for AI code execution with built-in timeout and resource limits; less operational overhead.
- Anthropic Artifacts + local Claude Desktop MCP – Use Claude's native code execution in isolated contexts without separate infrastructure.
- Firecracker/gVisor – Lower-level VM/container runtimes for custom sandbox implementations with stronger isolation guarantees.
- Temporal/Durable Execution Frameworks – Orchestrate agent tasks with built-in retry, timeout, and audit trails rather than raw sandboxing.