**Ranking's job is concentration, not inclusion.** The brief implies the CVE is missed because the ranker
excluded it. It did not: CVE-2023-23488's region sits at position 390 of 4,463, inside the 500-region budget,
and was examined. It goes unreported because the budget is spent on 500 regions when 50 would do, and 500
is unaffordable at 6.63 s per family per region. So the ranker's success metric is not "is the CVE in the
budget" — it already is — but **"how small can the budget be while the CVE stays in it"**. That is a
different objective, and it is the one that makes a scan finish.
**The gap: nothing above says what the evidence IS.** "Sink shape" and "cleansing on the call" are named,
not defined, and a heuristic that is not defined cannot be language-agnostic because there is nothing to
check for language leakage. The rest of this brief defines it.
Two things the measurements confirm and the plan should lean on harder:
- **The joins are cheap and must survive any ranker.** 22% of query cost, two of three CVEs. A ranker that
demotes field- or hook-carried regions because they show no direct source is a ranker that loses those
CVEs. The evidence vector below therefore carries the join's own stage-one result as a field.
- **84% of regions in one tier means any separation is progress**, and the separation does not need to be
clever to be large. A tier 0 that is merely exact already reorders the budget more than the current ranker
ever has.
## The evidence vector, defined
The unit is a **(region, family) pair**. For each, a fixed vector of fields is computed. Every field is
defined in terms of **fact-table categories** — source, sink, sanitizer, dispatch, access — never in terms of
a language's syntax, which is what makes the definition language-agnostic: any language with a fact table
gets the same vector, and a heuristic that mentions `$wpdb` or `wp_ajax_` has by construction left the
vector and must be rejected in review.
**Where it is computed matters as much as what it is.** The graph is already built for the arbiter, at 76 s
for 637 files. Extracting these fields is a CPG query **without dataflow** — call nodes, their arguments,
their enclosing methods, the call graph one hop out — which is milliseconds per call rather than 6.63 s per
request. The extractor is therefore a sibling of `taint.sc` that never calls `reachableByFlows`:
> **Tiering is the CPG query without dataflow. Arbitration is the CPG query with it. Same graph, same
> facts, two costs.**
That is the whole architecture in one line, and it is why the evidence is language-agnostic rather than
merely language-neutral-in-intent: the CPG normalises syntax across frontends, so "the argument of this call
is a literal" means the same thing in PHP, Python and C.
### Sink evidence — from `[[sink]]` facts of family F
| field | definition | exactness |
|---|---|---|
| `sinks` | count of calls in scope matching a sink of F | exact |
| `shape` | per sink call, one of: **`literal`** (the vulnerable-position argument is a constant), **`bound`** (the call is a declared-safe form — a `parameterized` sanitizer fact wraps it, or its arity/shape matches the bound form the taint query already recognises), **`computed`** (the argument is an expression: concatenation, interpolation, a variable, a call result) | exact for `literal` and `bound`; `computed` is the residue |
| `cleansed_on_call` | per sink call, whether a sanitizer of F is an **ancestor of the vulnerable-position argument in the AST** — not merely present in the same function | exact, and this is the field a text scan gets wrong: `esc_sql` in scope on a different statement is `false` here |
### Source evidence — from `[[source]]` facts and the entry-point contract
| field | definition | exactness |
|---|---|---|
| `source_local` | a modelled source expression occurs in the region's own body | exact |
| `source_near` | a modelled source occurs in a method within k call-graph hops of the region (k = the arbiter's `callDepth`) | exact for the graph the arbiter will use |
| `entry` | the region is an entry point per the mapper, so its parameters are untrusted by contract | exact |
| `access` | the declared access level, **with provenance**: `declared` (a registration or route contract says so) or `inferred` (nothing found) — because "public" meaning "no decorator found" is the false positive the project has already paid for | exact |
| `carried` | the region reads a **field** whose assignment is fed by a source anywhere in the file, or a **dispatch** value whose registered producer is — i.e. stage one of the two-stage join, which is already computed and memoised, reused here as evidence | exact where computed; absent (not false) where the join was not run |
### Path evidence — cheap structural proxies for what dataflow would establish
| field | definition |
|---|---|
| `distance` | fewest call-graph hops from any source (local, near, entry parameter, or carried) to any sink of F: 0 = same statement, 1 = same method, 2+ = across calls, ∞ = no source found |
| `cleansing_between` | any sanitizer of F occurs on a call-graph path between a source and a sink — a weaker, cheaper version of `cleansed_on_call` that catches cleansing done in a helper |
### Structural and prior evidence
| field | definition |
|---|---|
| `shipped` | the project's own build declaration names this file (existing `shipped.py`) |
| `family_in_repo` | any sink of F exists **anywhere** in the repository |
| `prior` | a committed baseline recorded a finding at this site, or the site was in an exploration slice before |
## The tiers, defined as predicates over the vector
| tier | predicate | role |
|---|---|---|
| **0** | `sinks == 0` in the reachable scope, **or**`family_in_repo == false` | **exclude** — exact; the only tier that removes work |
| 1 | `sinks > 0` and no `source_local`, `source_near`, `entry`, or `carried` | ask last — nothing untrusted can arrive |
| 2 | a source exists, but **every** sink call is `bound` or `cleansed_on_call` | ask late — a flow may exist and will corroborate, not entail |
| 3 | a source exists and **some** sink call is `computed` and not `cleansed_on_call` | ask first |
| 3★ | tier 3 **and** (`access == declared public` or `distance ≤ 1` or `carried`) | ask very first |
Two properties are load-bearing and must hold in every implementation:
1.**Only tier 0 excludes; every other tier orders.** So the only place exactness is *required* is tier 0,
and tier 0's predicate has a proof: a family with no sink in reach cannot produce a flow, in any language,
under any dataflow model. Above tier 0, being wrong costs position, and `regions_truncated` reports what
position cost.
2.**Tier 0's scope must match the arbiter's.** At `callDepth = 0` the scope is the region; at depth k it is
the region plus its reachable methods. A tier 0 computed on the file when the arbiter will look k hops
out is not exact and must not be called so. The repository-wide form (`family_in_repo == false`) is exact
at every depth and is the cheap first cut — it alone removes all 487 `deserialization` requests on `pmpro`.
**Within a tier**, order by a score. In phase 2 that score is a fixed weighted sum over the vector, published
in the manifest so two runs agree. In phase 3 it is the model's ordering **of the same vector**, which is
what makes the two comparable: same input, different ordering function, one held-out metric.
## Where the model helps, and where it must not be allowed to
The vector above is exact wherever exactness was cheap. What remains genuinely uncertain is narrower than
"ranking":
- **Ambiguous cleansing.** `cleansed_on_call` is exact when the sanitizer wraps the argument directly. It is
`false` — correctly, but unhelpfully — when cleansing happens two statements earlier into a variable that is
then interpolated. Deciding whether *that* cleansing reaches *this* call is reading the code, and it is the
single largest source of tier-2/tier-3 misplacement.
- **Unfamiliar shapes.** A sink call whose form the `bound` rule does not recognise, in a framework with no
facts yet. The model can say "this looks bound" as an *ordering* opinion; it cannot add a `bound` fact,
because a fact is policy.
- **Within-tier priority** when the fixed score ties, which on a real repository it will, constantly.
And the boundaries:
- **The model never computes tier 0.** Exclusion is exact or it is a silent miss, and a model's "no sink
here" is not a proof.
- **The model never sees the question "is this vulnerable".** It sees "which of these is worth an expensive
query", with the vector and the sink call's source text. Adjudication is the arbiter's, and keeping it
there is what keeps the gates byte-identical.
- **The model's input is the vector plus text, never the arbiter's verdict** on the same run — that is the
closed loop feeding on itself.
## Metrics, so every phase can fail
| metric | definition | phase |
|---|---|---|
| `position(cve)` | rank position of each pinned CVE's (region, family) pair | 0 → all |
| `requests_issued` | taint requests after tiering | 1 |
| `budget_at_recall` | the smallest K such that every pinned CVE is in the top K — the concentration metric | 2, 3 |
| `time_to_complete` | wall clock for the taint query at that K | 2, 3 |
| `held_out_position` | `position(cve)` on a repository excluded from development of the change | 2, 3, 5 |
| `exploration_yield` | findings per region in the exploration slice versus in the top-K — the direct measure of what the ranker is missing | 4 |
`budget_at_recall` is the one that decides the release question. Today it is ≥ 390 on `pmpro`. If phase 2
takes it below 50, the scan finishes in minutes and the model is a refinement; if it does not, the model is
