95 lines
3.9 KiB
Markdown
95 lines
3.9 KiB
Markdown
# Entry-Point Detection — Problem & Architecture
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## 1) Why this exists
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Container images rarely expose their *real* workload directly. Shell wrappers, init shims, supervisors, or language launchers often sit between the Dockerfile `ENTRYPOINT`/`CMD` values and the program you actually care about. Stella Ops needs a deterministic, explainable way to map any container image (or running container) to a single logical entry point that downstream systems can reason about.
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We define the target artefact as the tuple below:
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```jsonc
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{
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"type": "java|dotnet|go|python|node|ruby|php-fpm|c/c++|rust|nginx|supervisor|other",
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"resolvedBinary": "/app/app.jar | /app/app.dll | /app/server | /usr/local/bin/node",
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"args": ["..."],
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"confidence": 0.00..1.00,
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"evidence": [
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"why we believe this"
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],
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"chain": [
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{"from": "/bin/sh -c", "to": "/entrypoint.sh", "why": "ENTRYPOINT shell-form"},
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{"from": "/entrypoint.sh", "to": "java -jar orders.jar", "why": "exec \"$@\" with java default"}
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]
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}
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```
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Constraints:
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- Static first: no `/proc`, no `ptrace`, no customer code execution when scanning images.
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- Honour Docker/OCI precedence (`ENTRYPOINT` vs `CMD`, shell- vs exec-form, Windows `Shell` overrides).
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- Work on distroless and multi-arch images as well as traditional distro bases.
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- Emit auditable evidence and reduction chains so policy decisions are explainable.
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## 2) Dual-mode architecture
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The scanner exposes a single façade but routes to two reducers:
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```
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Scanner.EntryTrace/
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Common/
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OciImageReader.cs
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OverlayVfs.cs
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Heuristics/
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Models/
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Dynamic/ProcReducer.cs // running container
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Static/ImageReducer.cs // static image inference
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```
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Selection logic:
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```csharp
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IEntryReducer reducer = container.IsRunning
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? new ProcReducer()
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: new ImageReducer();
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var result = reducer.TraceAndReduce(ct);
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```
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Both reducers publish a harmonised `EntryTraceResult`, allowing downstream modules (Policy Engine, Vuln Explorer, Export Center) to consume the same shape regardless of data source.
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## 3) Pipeline overview
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### 3.1 Static images
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1. Pull or load OCI image.
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2. Compose final argv (`ENTRYPOINT ++ CMD`), respecting shell overrides.
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3. Overlay layers with whiteout support via a lazy virtual filesystem.
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4. Resolve paths, shebangs, wrappers, and scripts until a terminal candidate emerges.
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5. Classify runtime family, identify application artefact, score confidence, and emit evidence.
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### 3.2 Running containers
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1. Capture real exec / fork events and build an exec graph.
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2. Locate steady-state processes (long-lived, owns listeners, not a shim).
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3. Collapse wrappers using the same catalogue as static mode.
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4. Cross-check with static heuristics to tighten confidence.
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### 3.3 Shared components
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- **ShellFlow static analyser** handles script idioms (`set --`, `exec "$@"`, branch rewrites).
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- **Wrapper catalogue** recognises shells, init shims, supervisors, and package runners.
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- **Runtime detectors** plug in per language/framework (Java, .NET, Node, Python, PHP-FPM, Ruby, Go, Rust, Nginx, C/C++).
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- **Score calibrator** turns detector raw scores into a unified 0..1 confidence.
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## 4) Document map
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The entry-point playbook is now split into focused guides:
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| Document | Purpose |
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| --- | --- |
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| `entrypoint-static-analysis.md` | Overlay VFS, argv composition, wrapper reduction, scoring. |
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| `entrypoint-dynamic-analysis.md` | Observational Exec Graph for running containers. |
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| `entrypoint-shell-analysis.md` | ShellFlow static analyser and script idioms. |
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| `entrypoint-runtime-overview.md` | Detector contracts, helper utilities, calibration, integrations. |
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| `entrypoint-lang-*.md` | Runtime-specific heuristics (Java, .NET, Node, Python, PHP-FPM, Ruby, Go, Rust, C/C++, Nginx, Deno, Elixir/BEAM, Supervisor). |
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Use this file as the landing page; each guide can be read independently when implementing or updating a specific component.
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