AgentSight is a observability tool designed specifically for monitoring LLM agent behavior through SSL/TLS traffic interception and process monitoring. Unlike traditional application-level instrumentation, AgentSight observes at the system boundary using eBPF technology, providing comprehensive insights into AI agent interactions with minimal performance overhead.

✨ Zero Instrumentation Required - No code changes, no new dependencies, no SDKs. Works with any AI framework or application out of the box.

wget https://github.com/eunomia-bpf/agentsight/releases/latest/download/agentsight && chmod +x agentsight
# Record agent behavior from claude
sudo ./agentsight record -c "claude"
# Record agent behavior from gemini-cli (comm is "node")
sudo ./agentsight record -c "node"
# For Python AI tools
sudo ./agentsight record -c "python"
# Record claude or gemini activity with NVM Node.js, if bundle OpenSSL statically
sudo ./agentsight record --binary-path /usr/bin/node -c node

Visit http://127.0.0.1:7395 to view the recorded data.

Real-time process tree visualization showing AI agent interactions and file operations

Real-time timeline visualization showing AI agent interactions and system calls

Real-time metrics visualization showing AI agent memory and CPU usage

AgentSight captures critical interactions that application-level tools miss:

• Subprocess executions that bypass instrumentation
• Raw encrypted payloads before agent processing
• File operations and system resource access
• Cross-agent communications and coordination

┌─────────────────────────────────────────────────┐
│              AI Agent Runtime                   │
│   ┌─────────────────────────────────────────┐   │
│   │    Application-Level Observability      │   │
│   │  (LangSmith, Helicone, Langfuse, etc.)  │   │
│   │         🔴 Can be bypassed               │   │
│   └─────────────────────────────────────────┘   │
│                     ↕ (Can be bypassed)         │
├─────────────────────────────────────────────────┤ ← System Boundary
│  🟢 AgentSight eBPF Monitoring (Kernel-level)   │
│  ┌─────────────────┐  ┌─────────────────────┐   │
│  │   SSL Traffic   │  │    Process Events   │   │
│  │   Monitoring    │  │    Monitoring       │   │
│  └─────────────────┘  └─────────────────────┘   │
└─────────────────────────────────────────────────┘
                      ↓
┌─────────────────────────────────────────────────┐
│         Rust Streaming Analysis Framework       │
│  ┌─────────────┐  ┌──────────────┐  ┌────────┐  │
│  │   Runners   │  │  Analyzers   │  │ Output │  │
│  │ (Collectors)│  │ (Processors) │  │        │  │
│  └─────────────┘  └──────────────┘  └────────┘  │
└─────────────────────────────────────────────────┘
                      ↓
┌─────────────────────────────────────────────────┐
│           Frontend Visualization                │
│     Timeline • Process Tree • Event Logs       │
└─────────────────────────────────────────────────┘

1. eBPF Data Collection (Kernel Space)

   • SSL Monitor: Intercepts SSL/TLS read/write operations via uprobe hooks
   • Process Monitor: Tracks process lifecycle and file operations via tracepoints
   • <3% Performance Overhead: Operates below application layer with minimal impact

2. Rust Streaming Framework (User Space)

   • Runners: Execute eBPF programs and stream JSON events (SSL, Process, Agent, Combined)
   • Analyzers: Pluggable processors for HTTP parsing, chunk merging, filtering, logging
   • Event System: Standardized event format with rich metadata and JSON payloads

3. Frontend Visualization (React/TypeScript)

   • Interactive timeline, process tree, and log views
   • Real-time data streaming and analysis
   • See "Web Interface Access" section for details

eBPF Programs → JSON Events → Runners → Analyzer Chain → Frontend/Storage/Output

• Linux kernel: 4.1+ with eBPF support (5.0+ recommended)
• Root privileges: Required for eBPF program loading
• Rust toolchain: 1.88.0+ (for building collector)
• Node.js: 18+ (for frontend development)
• Build tools: clang, llvm, libelf-dev

AgentSight runs in Docker with --privileged for eBPF, --pid=host to access host processes, -v /sys:/sys:ro for process monitoring, and -v /usr:/usr:ro -v /lib:/lib:ro for SSL library access (required to attach uprobes to shared libraries like libssl.so). Example:

docker run --privileged --pid=host --network=host \
  -v /sys:/sys:ro -v /usr:/usr:ro -v /lib:/lib:ro \
  -v $(pwd)/logs:/logs \
  ghcr.io/eunomia-bpf/agentsight:latest \
  record --comm claude --log-file /logs/record.log

# Clone repository with submodules
git clone https://github.com/eunomia-bpf/agentsight.git --recursive
cd agentsight

# Install system dependencies (Ubuntu/Debian)
make install

# Build all components (frontend, eBPF, and Rust)
make build

# Or build individually:
# make build-frontend  # Build frontend assets
# make build-bpf       # Build eBPF programs
# make build-rust      # Build Rust collector

# Combined SSL and process monitoring with web interface
sudo ./agentsight trace --ssl --process --server

# Custom port and log file
sudo ./agentsight record -c "python" --server-port 8080 --log-file /tmp/agent.log

For Node.js installed via NVM, use the --binary-path option:

# Monitor Node.js applications with statically-linked SSL
sudo ./agentsight ssl --binary-path ~/.nvm/versions/node/v20.0.0/bin/node --comm node

# Record with custom binary path
sudo ./agentsight record -c node -- --binary-path ~/.nvm/versions/node/v20.0.0/bin/node

# Run eBPF programs directly for development/testing
sudo ./bpf/sslsniff --binary-path ~/.nvm/versions/node/v20.0.0/bin/node --verbose
sudo ./bpf/process -c python

All monitoring commands with --server flag provide web visualization at:

• Timeline View: http://127.0.0.1:7395/timeline
• Process Tree: http://127.0.0.1:7395/tree
• Raw Logs: http://127.0.0.1:7395/logs

Q: How does AgentSight differ from traditional APM tools? A: AgentSight operates at the kernel level using eBPF, providing system-level monitoring that is independent of application code. Traditional APM requires instrumentation that can be modified or disabled.

Q: What's the performance impact? A: Less than 3% CPU overhead due to optimized eBPF kernel-space data collection.

Q: Can agents detect they're being monitored?
A: Detection is extremely difficult since monitoring occurs at the kernel level without code modification.

Q: Which Linux distributions are supported? A: Any distribution with kernel 4.1+ (5.0+ recommended). Tested on Ubuntu 20.04+, CentOS 8+, RHEL 8+.

Q: Can I monitor multiple agents simultaneously?
A: Yes, use combined monitoring modes for concurrent multi-agent observation with correlation.

Q: How do I filter sensitive data?
A: Built-in analyzers can remove authentication headers and filter specific content patterns.

Q: Why doesn't AgentSight capture traffic from my NVM Node.js application? A: NVM Node.js binaries statically link OpenSSL instead of using system libraries. See the "NVM Node.js Applications" section for --binary-path usage examples.

Q: "Permission denied" errors
A: Ensure you're running with sudo or have CAP_BPF and CAP_SYS_ADMIN capabilities.

Q: "Failed to load eBPF program" errors A: Verify kernel version meets requirements (see Prerequisites). Update vmlinux.h for your architecture if needed.

We welcome contributions! After cloning and building (see Installation above), you can:

# Run tests
make test

# Frontend development server
cd frontend && npm run dev

# Build debug versions with AddressSanitizer
make -C bpf debug

• CLAUDE.md - Project guidelines and architecture
• collector/DESIGN.md - Framework design details
• docs/why.md - Problem analysis and motivation

MIT License - see LICENSE for details.

💡 The Future of AI Observability: As AI agents become more autonomous and capable of self-modification, traditional observability approaches become insufficient. AgentSight provides independent, system-level monitoring for safe AI deployment at scale.