eBPF is a technology that enables the dynamic injection of custom, sandboxed programs directly into the Linux kernel at runtime. It fundamentally changes the operating system's behavior without requiring kernel source code modifications or rebooting. By attaching to kernel hooks and events, eBPF programs can safely and efficiently inspect, filter, and manipulate system-wide data, including network packets, system calls, and function entry points, all within a strictly verified execution context.
Glossary
eBPF

What is eBPF?
eBPF is a revolutionary kernel technology that allows sandboxed programs to run in the Linux kernel without changing kernel source code, enabling deep, high-performance observability and security enforcement for agent processes.
For autonomous agent sandboxing, eBPF provides a powerful, non-invasive mechanism for runtime security and deep observability. It allows a Policy Enforcement Point to monitor agent processes at the syscall level, enforcing Least Privilege Execution by detecting and blocking anomalous behaviors like unauthorized file access or network connections. This kernel-level visibility, operating below the container or MicroVM, is critical for detecting Container Escape attempts and implementing fine-grained Egress Filtering without the performance overhead of traditional security agents.
Key Features of eBPF
eBPF revolutionizes Linux kernel programming by enabling sandboxed, high-performance programs to run directly in the kernel without modifying source code. These capabilities make it the foundation for next-generation observability, security, and networking for autonomous agent infrastructure.
In-Kernel Sandboxed Execution
eBPF programs run in a strictly sandboxed virtual machine inside the Linux kernel. Before loading, every program passes through a verifier that statically analyzes the bytecode to guarantee safety: no infinite loops, no out-of-bounds memory access, and no unauthorized kernel state modification. This ensures that even a misbehaving eBPF program cannot crash the kernel or compromise system stability, making it safe for production agent environments.
Just-In-Time Compilation
eBPF bytecode is translated into native machine instructions by a JIT compiler in the kernel. This means eBPF programs execute at near-native CPU speed, avoiding the overhead of interpretation. For agentic systems requiring real-time syscall monitoring or network packet filtering, JIT compilation ensures observability instrumentation adds negligible latency to critical paths.
Dynamic Kernel Instrumentation
eBPF enables runtime attachment to predefined hooks throughout the kernel without rebooting or recompiling. Key hook types include:
- kprobes/kretprobes: Dynamic tracing of any kernel function entry or return
- tracepoints: Stable, pre-defined instrumentation points in kernel subsystems
- uprobes: User-space function tracing for agent process introspection
- USDT probes: User-level statically defined tracing markers This allows DevSecOps teams to instrument agent behavior on demand.
Efficient Data Structures: eBPF Maps
eBPF programs use maps to store and share data between kernel and user space. These are generic key-value data structures with various backends optimized for different access patterns:
- Hash maps for fast lookups
- Ring buffers for lossless, high-throughput event streaming
- Per-CPU arrays for lock-free concurrent access
- LRU maps for bounded memory usage with automatic eviction Maps enable stateful monitoring of agent syscall patterns across multiple events.
Helper Functions and Tail Calls
eBPF programs are restricted from calling arbitrary kernel functions for safety. Instead, they invoke a curated set of helper functions that provide controlled access to kernel capabilities:
bpf_get_current_pid_tgid()to identify the calling processbpf_perf_event_output()to stream data to user spacebpf_tail_call()to chain programs together without returning to user space Tail calls enable modular, composable eBPF logic for complex agent security policies.
CO-RE: Compile Once, Run Everywhere
Compile Once, Run Everywhere (CO-RE) solves the portability challenge of eBPF across different kernel versions. It uses BTF (BPF Type Format) metadata to relocate field offsets and structure layouts at load time. A single compiled eBPF object can run on kernels from 5.4 to the latest release without recompilation, dramatically simplifying deployment across heterogeneous agent host fleets.
Frequently Asked Questions
Explore the core concepts of eBPF, the revolutionary kernel technology that enables sandboxed programmability for high-performance observability and security enforcement in agentic systems.
eBPF (extended Berkeley Packet Filter) is a revolutionary technology that allows sandboxed programs to run in a privileged context, such as the Linux kernel, without changing kernel source code or loading kernel modules. It works by enabling developers to write programs in a restricted C-like language, which are then compiled to eBPF bytecode. A verifier statically analyzes this bytecode to guarantee safety—ensuring no infinite loops, out-of-bounds memory access, or crashes—before a JIT (Just-In-Time) compiler translates it into native machine instructions for maximum performance. These programs attach to various kernel hooks, like system calls, network events, or tracepoints, allowing for deep, high-speed observability and enforcement directly in the kernel's execution path.
Enabling Efficiency, Speed & Accuracy
Intelligent Analysis, Decision & Execution
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Talk to Us
Search across company data
Give teams answers from docs, tickets, runbooks, and product data with sources and permissions.
Useful when people spend too long searching or get different answers from different systems.

Automate internal workflows
Use AI to route work, draft outputs, trigger actions, and keep approvals and logs in place.
Useful when repetitive work moves across multiple tools and teams.

Add AI to products and internal tools
Build assistants, guided actions, or decision support into the software your team or customers already use.
Useful when AI needs to be part of the product, not a separate tool.
Related Terms
eBPF is a foundational technology for modern sandboxing. These related concepts form the security stack that protects autonomous agent execution environments.
Seccomp Profile
A Linux kernel facility that restricts a process to a predefined set of system calls. Once applied, the process enters a restricted state that cannot be reversed. For agent sandboxing, seccomp profiles prevent a compromised agent from making dangerous syscalls like ptrace, mount, or reboot, drastically reducing the kernel attack surface. eBPF programs can dynamically enforce and monitor seccomp violations in real time.
MicroVM
A minimalist virtual machine that uses hardware virtualization for strong isolation while stripping the guest kernel of unnecessary drivers. Unlike traditional VMs, MicroVMs boot in milliseconds and consume minimal memory. Firecracker, AWS's open-source MicroVM, runs Lambda and Fargate workloads. When combined with eBPF for host-level observability, MicroVMs provide defense-in-depth for agent execution.
Runtime Security
The practice of monitoring and protecting execution environments in real time by detecting anomalous behavior. Key signals include:
- Unexpected system call sequences
- Unauthorized file access patterns
- Suspicious network connections to unknown IPs
- Process tree anomalies indicating privilege escalation
eBPF enables runtime security by attaching probes directly to kernel functions without loading kernel modules, providing deep visibility with minimal performance overhead.
Policy Enforcement Point
A PEP intercepts an agent's request and enforces an authorization decision before the action executes. In an eBPF-augmented sandbox, the PEP operates at the kernel level, blocking unauthorized syscalls before they reach hardware. This architecture follows the zero-trust principle: every action is verified, regardless of where the agent runs. Combined with Open Policy Agent (OPA) for decision logic, PEPs create a decoupled, auditable enforcement layer.
Execution Allowlisting
A security control that prevents execution of any binary or script not on a pre-approved list. For agent sandboxes, this means:
- Blocking unauthorized tool installations
- Preventing
curl | bash-style attacks - Stopping interpreters from running arbitrary code
eBPF programs enforce allowlisting by hooking the execve syscall and validating the binary's hash or path against a known-good manifest before allowing execution to proceed.

About the author
Prasad Kumkar
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
Partnered with leading AI, data, and software stack.
How We Work
Custom AI workflows for your Business
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
01
Review the use case
We understand the task, the users, and where AI can actually help.
Read more02
Pick the right approach
We define what needs search, automation, or product integration.
Read more03
Build the first useful version
We implement the part that proves the value first.
Read more04
Improve from there
We add the checks and visibility needed to keep it useful.
Read moreThe first call is a practical review of your use case and the right next step.
Talk to Us