<p>This is Part 1 of the container escape telemetry series. The <a href="../intro">series overview</a> has the project goals, key findings, and reading guide. If you’re already comfortable with namespaces, cgroups, capabilities, and how eBPF ring buffers work, skip ahead to <a href="../methodology">Part 2: Methodology and Tool Architecture</a>.</p>
<p>This is Part 2 of the container escape telemetry series (<a href="../intro">overview</a>). <a href="../isolation">Part 1</a> covered the isolation primitives and eBPF observability model. This post covers the lab architecture, the three tools under test, the 15 escape scenarios, and the detection coverage matrix. If you want to skip straight to what the telemetry actually looks like, jump to <a href="../deepdives">Part 3: Per-Scenario Deep Dives</a>.</p>
<p>This is Part 3 of the container escape telemetry series (<a href="../intro">overview</a>). <a href="../isolation">Part 1</a> covered isolation primitives and the eBPF observability model. <a href="../methodology">Part 2</a> covered the lab, the tools, and the detection coverage matrix. This post is the meat: per-scenario telemetry breakdowns showing what each tool actually captured, where the qualitative differences behind the checkmarks become concrete.</p>
How much telemetry do Tetragon, Falco, and Tracee actually generate? Per-scenario volume breakdowns, signal-to-noise analysis, production rate estimates, the Falco rule gap, S15 stress test results, and recommendations by threat model.
<p>This is Part 4 of the container escape telemetry series (<a href="../intro">overview</a>). <a href="../isolation">Part 1</a> covered isolation primitives and the eBPF observability model. <a href="../methodology">Part 2</a> covered the lab and detection coverage matrix. <a href="../deepdives">Part 3</a> walked through per-scenario telemetry. This post is about the operational questions: how much data do these tools produce, what percentage of it matters, and which tool should you actually…
<p>This is Part 5 of the container escape telemetry series (<a href="../intro">overview</a>). <a href="../isolation">Part 1</a> covered isolation primitives. <a href="../methodology">Part 2</a> covered the lab and tools. <a href="../deepdives">Part 3</a> was the per-scenario data. <a href="../production">Part 4</a> covered volume, signal-to-noise, and tool selection. This post is for the practitioner who just installed one of these tools and wants to know what to do next.</p>
<p>This is Part 6 of the container escape telemetry series (<a href="../intro">overview</a>). Parts <a href="../isolation">1</a>-<a href="../tuning">5</a> covered isolation primitives, methodology, per-scenario telemetry, production considerations, and tuning. This post takes the lab findings and pressure-tests them against a real threat actor operating in the wild right now.</p>
<p>As a detection engineer, container escapes have always fascinated me. Detections focused on control bypasses can be both extremely difficult to make and extremely valuable when they fire. The challenge is that most discussions about container runtime security focus on <em>whether</em> a tool detected an escape – a binary yes/no that doesn’t tell you much about the underlying telemetry that makes detection possible in the first place.</p>
