sprints and audit work
This commit is contained in:
StellaOps Bot
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Here’s a compact, practical blueprint for a **binary‑fingerprint store + trust‑scoring engine** that lets you quickly tell whether a system binary is patched, backported, or risky—even fully offline.
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# Why this matters (plain English)
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Package versions lie (backports!). Instead of trusting names like `libssl 1.1.1k`, we trust **what’s inside**: build IDs, section hashes, compiler metadata, and signed provenance. With that, we can answer: *Is this exact binary known‑good, known‑bad, or unknown—on this distro, on this date, with these patches?*
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---
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# Core concept
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* **Binary Fingerprint** = tuple of:
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* **Build‑ID** (ELF/PE), if present.
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* **Section‑level hashes** (e.g., `.text`, `.rodata`, selected function ranges).
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* **Compiler/Linker metadata** (vendor/version, LTO flags, PIE/RELRO, sanitizer bits).
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* **Symbol graph sketch** (optional, min‑hash of exported symbol names + sizes).
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* **Feature toggles** (FIPS mode, CET/CFI present, Fortify level, RELRO type, SSP).
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* **Provenance Chain** (who built it): Upstream → Distro vendor (with patchset) → Local rebuild.
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* **Trust Score**: combines provenance weight + cryptographic attestations + “golden set” matches + observed patch deltas.
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---
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# Minimal architecture (fits Stella Ops style)
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1. **Ingesters**
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* `ingester.distro`: walks repo mirrors or local systems, extracts ELF/PE, computes fingerprints, captures package→file mapping, vendor patch metadata (changelog, source SRPM diffs).
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* `ingester.upstream`: indexes upstream releases, commit tags, and official build artifacts.
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* `ingester.local`: indexes CI outputs (your own builds), in‑toto/DSSE attestations if available.
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2. **Fingerprint Store (offline‑ready)**
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* **Primary DB**: PostgreSQL (authoritative).
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* **Accelerator**: Valkey (ephemeral) for fast lookup by Build‑ID and section hash prefixes.
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* **Bundle Export**: signed, chunked SQLite/Parquet packs for air‑gapped sites.
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3. **Trust Engine**
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* Scores (0–100) per binary instance using:
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* Provenance weight (Upstream signed > Distro signed > Local unsigned).
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* Attestation presence/quality (in‑toto/DSSE, reproducible build stamp).
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* Patch alignment vs **Golden Set** (reference fingerprints for “fixed” and “vulnerable” builds).
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* Hardening baseline (RELRO/PIE/SSP/CET/CFI).
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* Divergence penalty (unexpected section deltas vs vendor‑declared patch).
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* Emits **Verdict**: `Patched`, `Likely Patched (Backport)`, `Unpatched`, `Unknown`, with rationale.
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4. **Query APIs**
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* `/lookup/by-buildid/{id}`
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* `/lookup/by-hash/{algo}/{prefix}`
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* `/classify` (batch): accepts an SBOM file list or live filesystem scan.
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* `/explain/{fingerprint}`: returns diff vs Golden Set and the proof trail.
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---
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# Data model (tables you can lift into Postgres)
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* `artifact`
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`(artifact_id PK, file_sha256, size, mime, elf_machine, pe_machine, ts, signers[])`
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* `fingerprint`
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`(fp_id PK, artifact_id, build_id, text_hash, rodata_hash, sym_sketch, compiler_vendor, compiler_ver, lto, pie, relro, ssp, cfi, cet, flags jsonb)`
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* `provenance`
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`(prov_id PK, fp_id, origin ENUM('upstream','distro','local'), vendor, distro, release, package, version, source_commit, patchset jsonb, attestation_hash, attestation_quality_score)`
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* `golden_set`
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`(golden_id PK, package, cve, status ENUM('fixed','vulnerable'), fp_ref, method ENUM('vendor-advisory','diff-sig','function-patch'), notes)`
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* `trust_score`
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`(fp_id, score int, verdict, reasons jsonb, computed_at)`
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Indexes: `(build_id)`, `(text_hash)`, `(rodata_hash)`, `(package, version)`, GIN on `patchset`, `reasons`.
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---
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# How detection works (fast path)
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1. **Exact match**
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Build‑ID hit → join `golden_set` → return verdict + reason.
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2. **Near match (backport mode)**
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No Build‑ID match → compare `.text`/`.rodata` and function‑range hashes against “fixed” Golden Set:
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* If patched function ranges match, mark **Likely Patched (Backport)**.
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* If vulnerable function ranges match, mark **Unpatched**.
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3. **Heuristic fallback**
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Symbol sketch + compiler metadata + hardening flags narrow candidate set; compute targeted function hashes only (don’t hash the whole file).
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---
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# Building the “Golden Set”
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* Sources:
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* Vendor advisories (per‑CVE “fixed in” builds).
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* Upstream tags containing the fix commit.
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* Distro SRPM diffs for backports (extract exact hunk regions; compute function‑range hashes pre/post).
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* Store **both**:
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* “Fixed” fingerprints (post‑patch).
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* “Vulnerable” fingerprints (pre‑patch).
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* Annotate evidence method:
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* `vendor-advisory` (strong), `diff-sig` (strong if clean hunk), `function-patch` (targeted).
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---
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# Trust scoring (example)
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* Base by provenance:
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* Upstream + signed + reproducible: **+40**
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* Distro signed with changelog & SRPM diff: **+30**
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* Local unsigned: **+10**
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* Attestations:
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* Valid DSSE + in‑toto chain: **+20**
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* Reproducible build proof: **+10**
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* Golden Set alignment:
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* Matches “fixed”: **+20**
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* Matches “vulnerable”: **−40**
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* Partial (patched functions match, rest differs): **+10**
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* Hardening:
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* PIE/RELRO/SSP/CET/CFI each **+2** (cap +10)
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* Divergence penalties:
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* Unexplained text‑section drift **−10**
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* Suspicious toolchain fingerprint **−5**
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Verdict bands: `≥80 Patched`, `65–79 Likely Patched (Backport)`, `35–64 Unknown`, `<35 Unpatched`.
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---
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# CLI outline (Stella Ops‑style)
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```bash
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# Index a filesystem or package repo
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stella-fp index /usr/bin /lib --out fp.db --bundle out.bundle.parquet
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# Score a host (offline)
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stella-fp classify --fp-store fp.db --golden golden.db --out verdicts.json
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# Explain a result
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stella-fp explain --fp <fp_id> --golden golden.db
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# Maintain Golden Set
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stella-fp golden add --package openssl --cve CVE-2023-XXXX --status fixed --from-srpm path.src.rpm
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stella-fp golden add --package openssl --cve CVE-2023-XXXX --status vulnerable --from-upstream v1.1.1k
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```
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---
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# Implementation notes (ELF/PE)
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* **ELF**: read Build‑ID from `.note.gnu.build-id`; hash `.text` and selected function ranges (use DWARF/eh_frame or symbol table when present; otherwise lightweight linear‑sweep with sanity checks). Record RELRO/PIE from program headers.
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* **PE**: use Debug Directory (GUID/age) and Section Table; capture CFG/ASLR/NX/GS flags.
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* **Function‑range hashing**: normalize NOPs/padding, zero relocation slots, mask address‑relative operands (keeps hashes stable across vendor rebuilds).
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* **Performance**: cache per‑section hash; only compute function hashes when near‑match needs confirmation.
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---
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# How this plugs into your world
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* **Sbomer/Vexer**: attach trust scores & verdicts to components in CycloneDX/SPDX; emit VEX statements like “Fixed by backport: evidence=diff‑sig, source=Astra/RedHat SRPM.”
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* **Feedser**: when CVE feed says “vulnerable by version,” override with binary proof from Golden Set.
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* **Policy Engine**: gate deployments on `verdict ∈ {Patched, Likely Patched}` OR `score ≥ 65`.
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---
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# Next steps you can action today
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1. Create schemas above in Postgres; scaffold a small `stella-fp` Go/.NET tool to compute fingerprints for `/bin`, `/lib*` on one reference host (e.g., Debian + Alpine).
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2. Hand‑curate a **pilot Golden Set** for 3 noisy CVEs (OpenSSL, glibc, curl). Store both pre/post patch fingerprints and 2–3 backported vendor builds each.
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3. Wire a `classify` step into your CI/CD and surface the **verdict + rationale** in your VEX output.
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If you want, I can drop in starter code (C#/.NET 10) for the fingerprint extractor and the Postgres schema migration, plus a tiny “function‑range hasher” that masks relocations and normalizes padding.
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Here’s a tight, practical plan to add **deterministic binary‑patch evidence** to Stella Ops by integrating **B2R2** (IR lifter/disassembler for .NET/F#) into your scanning pipeline, then feeding stable “diff signatures” into your **VEX Resolver**.
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# What & why (one minute)
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* **Goal:** Prove (offline) that a distro backport truly patched a CVE—even if version strings look “vulnerable”—by comparing *what the CPU will execute* before/after a patch.
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* **How:** Lift binaries to a normalized IR with **B2R2**, canonicalize semantics (strip address noise, relocations, NOPs, padding), **bucket** by function and **hash** stable opcode/semantics. Patch deltas become small, reproducible evidence blobs your VEX engine can consume.
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# High‑level flow
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1. **Collect**: For each package/artifact, grab: *installed binary*, *claimed patched reference* (vendor’s patched ELF/PE or your golden set), and optional *original vulnerable build*.
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2. **Lift**: Use B2R2 to disassemble → lift to **LIR**/**SSA** (arch‑agnostic).
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3. **Normalize** (deterministic):
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* Strip addrs/symbols/relocations; fold NOPs; normalize register aliases; constant‑prop + dead‑code elim; canonical call/ret; normalize PLT stubs; elide alignment/padding.
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4. **Segment**: Per‑function IR slices bounded by CFG; compute **stable function IDs** = `SHA256(package@version, build-id, arch, fn-cfg-shape)`.
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5. **Hashing**:
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* **Opcode hash**: SHA256 of normalized opcode stream.
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* **Semantic hash**: SHA256 of (basic‑block graph + dataflow summaries).
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* **Const set hash**: extracted immediate set (range‑bucketed) to detect patched lookups.
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6. **Diff**:
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* Compare (patched vs baseline) per function: unchanged / changed / added / removed.
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* For changed: emit **delta record** with before/after hashes and minimal edit script (block‑level).
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7. **Evidence object** (deterministic, replayable):
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* `type: "disasm.patch-evidence@1"`
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* inputs: file digests (SHA256/SHA3‑256), Build‑ID, arch, toolchain versions, B2R2 commit, normalization profile ID
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* outputs: per‑function records + global summary
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* sign: DSSE (in‑toto link) with your offline key profile
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8. **Feed VEX**:
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* Map CVE→fix‑site heuristics (from vendor advisories/diff hints) to function buckets.
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* If all required buckets show “patched” (semantic hash change matches inventory rule), set **`affected=false, justification=code_not_present_or_not_reachable`** (CycloneDX VEX/CVE‑level) with pointer to evidence object.
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# Module boundaries in Stella Ops
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* **Scanner.WebService** (per your rule): host *lattice algorithms* + this disassembly stage.
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* **Sbomer**: records exact files/Build‑IDs in CycloneDX 1.6/1.7 SBOM (you’re moving to 1.7 soon—ensure `properties` include `disasm.profile`, `b2r2.version`).
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* **Feedser/Vexer**: consume evidence blobs; Vexer attaches VEX statements referencing `evidenceRef`.
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* **Authority/Attestor**: sign DSSE attestations; Timeline/Notify surface verdict transitions.
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# On‑disk schemas (minimal)
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```json
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{
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"type": "stella.disasm.patch-evidence@1",
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"subject": [{"name": "libssl.so.1.1", "digest": {"sha256": "<...>"}, "buildId": "elf:..."}],
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"tool": {"name": "stella-b2r2", "b2r2": "<commit>", "profile": "norm-v1"},
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"arch": "x86_64",
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"functions": [{
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"fnId": "sha256(pkg,buildId,arch,cfgShape)",
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"addrRange": "0x401000-0x40118f",
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"opcodeHashBefore": "<...>",
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"opcodeHashAfter": "<...>",
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"semanticHashBefore": "<...>",
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"semanticHashAfter": "<...>",
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"delta": {"blocksEdited": 2, "immDiff": ["0x7f->0x00"]}
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}],
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"summary": {"unchanged": 812, "changed": 6, "added": 1, "removed": 0}
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}
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```
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# Determinism controls
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* Pin **B2R2 version** and **normalization profile**; serialize the profile (passes + order + flags) and include it in evidence.
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* Containerize the lifter; record image digest in evidence.
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* For randomness (e.g., hash‑salts), set fixed zeros; set `TZ=UTC`, `LC_ALL=C`, and stable CPU features.
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* Replay manifests: list all inputs (file digests, B2R2 commit, profile) so anyone can re‑run and reproduce the exact hashes.
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# C# integration sketch (.NET 10)
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```csharp
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// StellaOps.Scanner.Disasm
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public sealed class DisasmService
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{
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private readonly IBinarySource _source; // pulls files + vendor refs
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private readonly IB2R2Host _b2r2; // thin wrapper over F# via FFI or CLI
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private readonly INormalizer _norm; // norm-v1 pipeline
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private readonly IEvidenceStore _evidence;
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public async Task<DisasmEvidence> AnalyzeAsync(Artifact a, Artifact baseline)
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{
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var liftedAfter = await _b2r2.LiftAsync(a.Path, a.Arch);
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var liftedBefore = await _b2r2.LiftAsync(baseline.Path, baseline.Arch);
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var fnAfter = _norm.Normalize(liftedAfter).Functions;
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var fnBefore = _norm.Normalize(liftedBefore).Functions;
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var bucketsAfter = Bucket(fnAfter);
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var bucketsBefore = Bucket(fnBefore);
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var diff = DiffBuckets(bucketsBefore, bucketsAfter);
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var evidence = EvidenceBuilder.Build(a, baseline, diff, _norm.ProfileId, _b2r2.Version);
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await _evidence.PutAsync(evidence); // write + DSSE sign via Attestor
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return evidence;
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}
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}
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```
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# Normalization profile (norm‑v1)
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* **Pass order:** CFG build → SSA → const‑prop → DCE → register‑rename‑canon → call/ret stub‑canon → PLT/plt.got unwrap → NOP/padding strip → reloc placeholder canon (`IMM_RELOC` tokens) → block re‑ordering freeze (cfg sort).
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* **Hash material:** `for block in topo(cfg): emit (opcode, operandKinds, IMM_BUCKETS)`; exclude absolute addrs/symbols.
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# Hash‑bucketing details
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* **IMM_BUCKETS:** bucket immediates by role: {addr, const, mask, len}. For `addr`, replace with `IMM_RELOC(section, relType)`. For `const`, clamp to ranges (e.g., table sizes).
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* **CFG shape hash:** adjacency list over block arity; keeps compiler‑noise from breaking determinism.
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* **Semantic hash seed:** keccak of (CFG shape hash || value‑flow summaries per def‑use).
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# VEX Resolver hookup
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* Extend rule language: `requires(fnId in {"EVP_DigestVerifyFinal", ...} && delta.immDiff.any == true)` → verdict `not_affected` with `justification="code_not_present_or_not_reachable"` and `impactStatement="Patched verification path altered constants"`.
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* If some required fix‑sites unchanged → `affected=true` with `actionStatement="Patched binary mismatch: function(s) unchanged"`, priority ↑.
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# Golden set + backports
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* Maintain per‑distro **golden patched refs** (Build‑ID pinned). If vendor publishes only source patch, build once with a fixed toolchain profile to derive reference hashes.
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* Backports: You’ll often see *different* opcode deltas with the *same* semantic intent—treat evidence as **policy‑mappable**: define acceptable delta patterns (e.g., bounds‑check added) and store them as **“semantic signatures”**.
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# CLI user journey (StellaOps standard CLI)
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```
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stella scan disasm \
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--pkg openssl --file /usr/lib/x86_64-linux-gnu/libssl.so.1.1 \
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--baseline @golden:debian-12/libssl.so.1.1 \
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--out evidence.json --attest
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```
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* Output: DSSE‑signed evidence; `stella vex resolve` then pulls it and updates the VEX verdicts.
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# Minimal MVP (2 sprints)
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**Sprint A (MVP)**
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* B2R2 host + norm‑v1 for x86_64, aarch64 (ELF).
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* Function bucketing + opcode hash; per‑function delta; DSSE evidence.
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* VEX rule: “all listed fix‑sites changed → not_affected”.
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**Sprint B**
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* Semantic hash; IMM bucketing; PLT/reloc canon; UI diff viewer in Timeline.
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* Golden‑set builder & cache; distro backport adapters (Debian, RHEL, Alpine, SUSE, Astra).
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# Risks & guardrails
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* Stripped binaries: OK (IR still works). PIE/ASLR: neutralized via reloc canon. LTO/inlining: mitigate with CFG shape + semantic hash (not symbol names).
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* False positives: keep “changed‑but‑harmless” patterns whitelisted via semantic signatures (policy‑versioned).
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* Performance: cache lifted IR by `(digest, arch, profile)`; parallelize per function.
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If you want, I can draft the **norm‑v1** pass list as a concrete F# pipeline for B2R2 and a **.proto/JSON‑Schema** for `stella.disasm.patch-evidence@1`, ready to drop into `scanner.webservice`.
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@@ -0,0 +1,85 @@
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**Stella Ops — Incremental Testing Enhancements (NEW since prior runs)**
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*Only net-new ideas and practices; no restatement of earlier guidance.*
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---
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## 1) Unit Testing — what to add now
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* **Semantic fuzzing for policies**: generate inputs that specifically target policy boundaries (quotas, geo rules, sanctions, priority overrides), not random fuzz.
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* **Time-skew simulation**: unit tests that warp time (clock drift, leap seconds, TTL expiry) to catch cache and signature failures.
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* **Decision explainability tests**: assert that every routing decision produces a minimal, machine-readable explanation payload (even if not user-facing).
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**Why it matters**: catches failures that only appear under temporal or policy edge conditions.
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---
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## 2) Module / Source-Level Testing — new practices
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* **Policy-as-code tests**: treat routing and ops policies as versioned code with diff-based tests (policy change → expected behavior delta).
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* **Schema evolution tests**: automatically replay last N schema versions against current code to ensure backward compatibility.
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* **Dead-path detection**: fail builds if conditional branches are never exercised across the module test suite.
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**Why it matters**: prevents silent behavior changes when policies or schemas evolve.
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---
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## 3) Integration Testing — new focus areas
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* **Production trace replay (sanitized)**: replay real, anonymized traces into integration environments to validate behavior against reality, not assumptions.
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* **Failure choreography tests**: deliberately stagger dependency failures (A fails first, then B recovers, then A recovers) and assert system convergence.
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* **Idempotency verification**: explicit tests that repeated requests under retries never create divergent state.
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**Why it matters**: most real outages are sequencing problems, not single failures.
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---
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## 4) Deployment / E2E Testing — additions
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* **Config-diff E2E tests**: assert that changing *only* config (no code) produces only the expected behavioral delta.
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* **Rollback lag tests**: measure and assert maximum time-to-safe-state after rollback is triggered.
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* **Synthetic adversarial traffic**: continuously inject malformed but valid-looking traffic post-deploy to ensure defenses stay active.
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**Why it matters**: many incidents come from “safe” config changes and slow rollback propagation.
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---
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## 5) Competitor Parity Testing — next-level
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* **Behavioral fingerprinting**: derive a compact fingerprint (outputs + timing + error shape) per request class and track drift over time.
|
||||
* **Asymmetric stress tests**: apply load patterns competitors are known to struggle with and verify Stella Ops remains stable.
|
||||
* **Regression-to-market alerts**: trigger alerts when Stella deviates from competitor norms in *either* direction (worse or suspiciously better).
|
||||
|
||||
**Why it matters**: parity isn’t static; it drifts quietly unless measured continuously.
|
||||
|
||||
---
|
||||
|
||||
## 6) New Cross-Cutting Standards to Enforce
|
||||
|
||||
* **Tests as evidence**: every integration/E2E run produces immutable artifacts suitable for audit or post-incident review.
|
||||
* **Deterministic replayability**: any failed test must be reproducible bit-for-bit within 24 hours.
|
||||
* **Blast-radius annotation**: every test declares what operational surface it covers (routing, auth, billing, compliance).
|
||||
|
||||
---
|
||||
|
||||
## Prioritized Checklist — This Week Only
|
||||
|
||||
**Immediate (1–2 days)**
|
||||
|
||||
1. Add decision-explainability assertions to core routing unit tests.
|
||||
2. Introduce time-skew unit tests for cache, TTL, and signature logic.
|
||||
3. Define and enforce idempotency tests on one critical integration path.
|
||||
|
||||
**Short-term (by end of week)**
|
||||
4. Enable sanitized production trace replay in one integration suite.
|
||||
5. Add rollback lag measurement to deployment/E2E tests.
|
||||
6. Start policy-as-code diff tests for routing rules.
|
||||
|
||||
**High-leverage**
|
||||
7. Implement a minimal competitor behavioral fingerprint and store it weekly.
|
||||
8. Require blast-radius annotations on all new integration and E2E tests.
|
||||
|
||||
---
|
||||
|
||||
### Bottom line
|
||||
|
||||
The next gains for Stella Ops testing are no longer about coverage—they’re about **temporal correctness, policy drift control, replayability, and competitive awareness**. Systems that fail now do so quietly, over time, and under sequence pressure. These additions close exactly those gaps.
|
||||
Reference in New Issue
Block a user