{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"hn-46706796","slug":"yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","name":"yolo-cage – AI coding agents that can't exfiltrate secrets","type":"repo","url":"https://github.com/borenstein/yolo-cage","page_url":"https://unfragile.ai/yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","categories":["automation"],"tags":["hackernews","show-hn"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"hn-46706796__cap_0","uri":"capability://safety.moderation.sandboxed.code.execution.with.secret.containment","name":"sandboxed-code-execution-with-secret-containment","description":"Executes AI-generated code in an isolated sandbox environment that prevents exfiltration of secrets through network requests, file system access, or environment variable leakage. Uses OS-level process isolation (likely seccomp, AppArmor, or similar kernel-level restrictions) combined with capability-dropping to create a cage that constrains what the executed code can do while still allowing legitimate computation and file I/O within safe boundaries.","intents":["Run AI-generated code without risking credential theft or data exfiltration","Allow coding agents to execute untrusted code safely in production environments","Prevent accidental or malicious secret leakage from LLM-generated scripts"],"best_for":["Teams deploying autonomous coding agents in security-sensitive environments","Developers building internal tools that execute LLM-generated code","Organizations with strict data governance requiring proof of secret containment"],"limitations":["Sandbox overhead adds latency to code execution (typically 50-500ms per invocation depending on kernel implementation)","Cannot execute code requiring privileged system calls (e.g., raw socket creation, direct hardware access)","Network isolation may break legitimate use cases requiring external API calls — requires explicit allowlisting","Performance degrades with high-frequency execution due to sandbox setup/teardown costs"],"requires":["Linux kernel with seccomp or AppArmor support (most modern distributions)","Appropriate kernel capabilities and permissions to create isolated processes","Runtime environment (Python, Node.js, etc.) compatible with the target code language"],"input_types":["code (Python, JavaScript, Bash, or other executable formats)","execution context (environment variables, working directory, file system mounts)"],"output_types":["code execution results (stdout, stderr)","return values or exit codes","file system artifacts (within sandbox boundaries)"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-46706796__cap_1","uri":"capability://safety.moderation.secret.filtering.and.redaction.at.execution.boundary","name":"secret-filtering-and-redaction-at-execution-boundary","description":"Intercepts and filters secrets (API keys, passwords, tokens, credentials) before they can be accessed by sandboxed code execution. Likely uses pattern matching, environment variable scanning, and credential detection to identify sensitive data in the execution context, then either redacts it, blocks access, or provides a sanitized version to the executing code. Works at the boundary between the host environment and the sandbox.","intents":["Prevent AI agents from accessing production credentials even if they request them","Automatically detect and block secret exfiltration attempts in generated code","Provide a safe execution environment where secrets are structurally unavailable"],"best_for":["CI/CD pipelines running AI-generated code with access to production secrets","Multi-tenant platforms where code isolation is critical","Development teams that want defense-in-depth against credential leakage"],"limitations":["Pattern-based detection may miss obfuscated or encoded secrets","Requires explicit configuration of what constitutes a 'secret' — no universal standard","Cannot protect against side-channel attacks (timing analysis, resource exhaustion to infer secrets)","Legitimate code that needs credentials must use explicit allowlisting or credential injection mechanisms"],"requires":["Configuration file or API to define secret patterns (regex, key names, etc.)","Access to environment variables and configuration sources in the host","Runtime hooks or middleware to intercept execution context"],"input_types":["environment variables","configuration files","credential stores or vaults","code execution context"],"output_types":["filtered/redacted execution context","access control decisions (allow/deny)","audit logs of secret access attempts"],"categories":["safety-moderation","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-46706796__cap_2","uri":"capability://code.generation.editing.ai.agent.code.generation.with.safety.constraints","name":"ai-agent-code-generation-with-safety-constraints","description":"Generates code through an AI agent (likely using an LLM like GPT-4 or Claude) that is constrained by safety guidelines and sandbox awareness. The agent understands the execution environment's limitations and generates code that respects the sandbox boundaries, avoids attempting secret access, and follows safe coding patterns. Likely uses prompt engineering, system instructions, or fine-tuning to make the agent aware of the cage constraints.","intents":["Generate code that is both functional and safe to execute in a sandboxed environment","Ensure AI-generated code respects security boundaries without requiring manual review","Allow developers to specify safety constraints that the agent incorporates into code generation"],"best_for":["Autonomous coding agents that need to generate production-safe code","Teams using LLMs for code generation but concerned about security implications","Developers building code generation pipelines with compliance requirements"],"limitations":["Agent may still generate code that attempts to exfiltrate secrets if not properly constrained","Safety constraints can reduce code functionality or performance if too restrictive","Requires careful prompt engineering to ensure agent understands sandbox limitations","No guarantee that agent will always respect constraints — still requires execution-time enforcement"],"requires":["LLM API access (OpenAI, Anthropic, or self-hosted model)","System prompts or instructions that define safety constraints","Integration with the sandbox execution environment to provide feedback"],"input_types":["natural language task descriptions","code context or examples","safety constraints or guidelines"],"output_types":["generated code (Python, JavaScript, Bash, etc.)","execution results","safety compliance metadata"],"categories":["code-generation-editing","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-46706796__cap_3","uri":"capability://safety.moderation.execution.context.isolation.with.controlled.resource.access","name":"execution-context-isolation-with-controlled-resource-access","description":"Isolates the execution context (file system, environment variables, network, system calls) for sandboxed code, providing controlled access to only necessary resources. Uses namespace isolation, chroot jails, or similar OS-level mechanisms to create a restricted view of the system. Resources are explicitly allowlisted or provided through controlled interfaces (e.g., mounted directories, injected credentials via secure channels).","intents":["Limit what files and system resources AI-generated code can access","Prevent code from modifying host system state or accessing sensitive files","Provide a minimal, controlled environment for code execution"],"best_for":["Multi-tenant platforms where code isolation is critical","Organizations running untrusted or AI-generated code in production","Developers building secure code execution services"],"limitations":["File system isolation adds complexity to code that needs to read/write files — requires explicit mount points","Network isolation breaks code that needs external API calls — requires explicit allowlisting or proxy setup","Resource limits (CPU, memory) may cause legitimate code to fail or timeout","Debugging sandboxed code is harder due to limited visibility into the execution environment"],"requires":["Linux kernel with namespace support (pid, network, mount, ipc, uts, user namespaces)","Ability to configure mount points and resource limits","Runtime environment compatible with the target code language"],"input_types":["code to execute","resource allowlist (files, network endpoints, system calls)","resource limits (CPU, memory, disk, file descriptors)"],"output_types":["code execution results","resource usage metrics","access violation logs"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-46706796__cap_4","uri":"capability://safety.moderation.audit.logging.and.security.event.tracking","name":"audit-logging-and-security-event-tracking","description":"Logs all execution events, access attempts, and security violations in the sandboxed environment. Tracks what code tried to do (successful and failed operations), what secrets it attempted to access, what network calls it made, and what system calls it invoked. Provides audit trails for compliance, debugging, and security analysis. Likely uses kernel-level tracing (auditd, eBPF) or runtime hooks to capture events.","intents":["Track what AI-generated code attempted to do during execution","Detect and log secret access attempts or exfiltration attempts","Provide audit trails for compliance and security investigations","Debug code failures by understanding what operations were blocked"],"best_for":["Organizations with compliance requirements (SOC 2, HIPAA, PCI-DSS)","Security teams investigating code execution incidents","Developers debugging why code failed in the sandbox"],"limitations":["Audit logging adds overhead to code execution (typically 10-50ms per operation)","High-volume logging can consume significant disk space and I/O bandwidth","Kernel-level tracing (auditd, eBPF) requires elevated privileges","Log analysis requires specialized tools and expertise to extract meaningful insights"],"requires":["Audit logging infrastructure (auditd, eBPF, or custom runtime hooks)","Log storage and retention system (files, database, log aggregation service)","Elevated privileges to install kernel-level tracing"],"input_types":["code execution events","system call traces","access control decisions","resource usage metrics"],"output_types":["structured audit logs (JSON, syslog format)","security event summaries","compliance reports"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"hn-46706796__cap_5","uri":"capability://safety.moderation.capability.based.access.control.for.code.operations","name":"capability-based-access-control-for-code-operations","description":"Implements fine-grained capability-based access control where code is granted specific capabilities (e.g., 'read from /tmp', 'write to output directory', 'call specific APIs') rather than broad permissions. Uses seccomp filters, AppArmor profiles, or SELinux policies to enforce capabilities at the kernel level. Code cannot perform operations outside its granted capabilities, even if it attempts to escalate privileges or use alternative system calls.","intents":["Grant code only the minimum permissions it needs to function","Prevent privilege escalation or capability abuse by sandboxed code","Enforce security policies at the kernel level where code cannot bypass them"],"best_for":["High-security environments where defense-in-depth is critical","Organizations running untrusted code from multiple sources","Teams that need provable security guarantees about code execution"],"limitations":["Capability configuration is complex and error-prone — requires deep security expertise","Overly restrictive capabilities can break legitimate code functionality","Debugging capability violations requires understanding kernel-level security policies","Different Linux distributions and kernel versions have varying capability support"],"requires":["Linux kernel with seccomp, AppArmor, or SELinux support","Security policy definitions (seccomp filters, AppArmor profiles, or SELinux policies)","Tools to test and validate capability policies"],"input_types":["code to execute","capability requirements (what operations code needs)","security policy definitions"],"output_types":["code execution results","capability violation logs","security policy compliance reports"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"high","permissions":["Linux kernel with seccomp or AppArmor support (most modern distributions)","Appropriate kernel capabilities and permissions to create isolated processes","Runtime environment (Python, Node.js, etc.) compatible with the target code language","Configuration file or API to define secret patterns (regex, key names, etc.)","Access to environment variables and configuration sources in the host","Runtime hooks or middleware to intercept execution context","LLM API access (OpenAI, Anthropic, or self-hosted model)","System prompts or instructions that define safety constraints","Integration with the sandbox execution environment to provide feedback","Linux kernel with namespace support (pid, network, mount, ipc, uts, user namespaces)"],"failure_modes":["Sandbox overhead adds latency to code execution (typically 50-500ms per invocation depending on kernel implementation)","Cannot execute code requiring privileged system calls (e.g., raw socket creation, direct hardware access)","Network isolation may break legitimate use cases requiring external API calls — requires explicit allowlisting","Performance degrades with high-frequency execution due to sandbox setup/teardown costs","Pattern-based detection may miss obfuscated or encoded secrets","Requires explicit configuration of what constitutes a 'secret' — no universal standard","Cannot protect against side-channel attacks (timing analysis, resource exhaustion to infer secrets)","Legitimate code that needs credentials must use explicit allowlisting or credential injection mechanisms","Agent may still generate code that attempts to exfiltrate secrets if not properly constrained","Safety constraints can reduce code functionality or performance if too restrictive","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.58,"quality":0.22,"ecosystem":0.46,"match_graph":0.25,"freshness":0.6,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:04.691Z","last_scraped_at":"2026-05-04T08:10:12.967Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","compare_url":"https://unfragile.ai/compare?artifact=yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s"}},"signature":"BsjiAD4PJ9va18xmDAmWXB1iTBcev+9Uq7fjatyseBAJ0nfqEKu2dXrZMSgPsvot+kYAwr7rNQkTV1mDcxPxBg==","signedAt":"2026-06-20T02:12:02.476Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","artifact":"https://unfragile.ai/yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","verify":"https://unfragile.ai/api/v1/verify?slug=yolo-cage-ai-coding-agents-that-can-t-exfiltrate-s","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}