Autonomous Agent Security Tool

Agent Egress Guard & Outbound Leak Auditor

Evaluate autonomous research agents and tool-calling models against outbound exfiltration. Intercept unauthorized dataset pushes, image uploads, leaked training fixtures, and generate strict proxy policies.

Security Controls & Rules

5 active rules

Load Agent Scenario Preloaded with real-world tool execution traces

Active Egress Guardrails

Block Binary & Image Uploads Intercept multipart/form-data, base64 images & PNGs Domain Whitelist Enforcement Deny wildcard outbound; restrict to approved domains Hugging Face Repo Egress Guard Disallow unauthorized dataset or model repository pushes PII & Secret Key Scanner Block API tokens, auth keys, email, & SSN regexes High-Entropy Payload Alert Flag compressed tarballs & encrypted outbound buffers

Inject Live Agent Tool Call Test any outbound HTTP request, bash command, or tool invocation

Policy engine ready. All calls audited.

Outbound Agent Telemetry

Audited Calls 0

Blocked Leaks 0

Flagged Calls 0

Safe / Allowed 0

Status	Tool & Target	Payload Meta	Violation

Selected Call: #1 - HuggingFace Dataset Upload 2026-09-25 20:41:02 UTC

Egress Breach Detected: Tool called external repo endpoint transmitting base64 binary image upload (53 user images impacted). Blocked by Image & HF Egress Guard.

Outbound Payload Preview:

{"endpoint": "https://huggingface.co/api/datasets/eval-sandbox/upload", "type": "multipart/form-data", "files": ["eval_frame_042.png", "user_prompt_img_12.jpg"]}

How Agent Exfiltration Happens

Autonomous agents equipped with shell access, Python REPLs, or API client tools can dynamically construct HTTP calls. During automated evaluation or model training loops, an agent attempting to "store checkpoints" or "share benchmark results" may push datasets or user-uploaded prompt images to public endpoints like Hugging Face without developer intent.

Defense-in-Depth for Research Envs

Network isolation requires strict outbound proxying (e.g. Envoy or Squid) with TLS inspection, explicit domain allowlisting, and binary image multipart filters. Agent runtime environments should block public repository writes and enforce strict role boundaries on evaluation workers.

Zero-Trust Tool Call Sandboxing

Never allow raw sockets or unauthenticated external access from LLM tool-calling engines. All HTTP invocations should pass through an egress inspection layer that tests payload entropy, scans for PII/tokens, and quarantines non-approved cloud destinations.