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JVM startup dominated a scan: a call per region per family put a ten-line file at 275s over three regions, and would have put a thousand regions at roughly fifty hours. The queries themselves are milliseconds once the CPG is loaded, so the cost was almost entirely process starts. scan_repository() is now collect -> batch -> arbitrate. The three .sc scripts accept a `requests` JSON map and answer all of them in one run, keeping the single-request form so the committed measurements stay reproducible byte-for-byte. Arbiters are untouched: each is handed a CpgResult whose `run` returns its own prefetched rows. The batcher builds parameters by calling request_params() extracted from taint.py, dominance.py and config_value.py rather than reconstructing them. A second copy that drifts from the arbiter's is the exact shape of the five family-assumption bugs the predecessor spec spent a session finding; there is now one definition per family and the batcher borrows it. Regions are also deduplicated by (path, function), collapsing the nameless entry-point rows that were producing `model:injection:?:10`. Measured on the same ten-line file: 275s -> 106s, three duplicate findings -> one `model:injection:ping:10`, rung unchanged at model_entailed. Gates byte-identical. Server mode is recorded as task 2.3, deliberately sequenced after the repository measurement: whether the remaining ~100s floor is worth a process model, a weakened subprocess seam and a Scala-evaluating HTTP endpoint depends on a build-time-to-query-time ratio only 2.2 produces. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
62 lines
2.8 KiB
Python
62 lines
2.8 KiB
Python
// Security settings and the literal values they are given (model-grounded-detection Req 6.3).
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//
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// A configuration bug has no flow and no guard: `CORS(app, origins="*")` is dangerous because of the value.
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// This query reports each setting call with its arguments split into literals (which the model can evaluate)
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// and non-literals (which it cannot -- those become `corroborated`, never silently safe).
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//
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// Parameters: cpgFile, settings, function (optional).
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// Output: fenced JSON array of {setting, line, method, args, literalArgs}.
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// BATCHED, like taint.sc. Single-request form kept for the committed measurements.
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@main def exec(cpgFile: String, settings: String = "", function: String = "", requests: String = "") = {
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importCpg(cpgFile)
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def split(raw: String): List[String] = raw.split(",").map(_.trim).filter(_.nonEmpty).toList
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def rowsFor(settingsS: String, functionS: String): List[ujson.Obj] = {
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val names = split(settingsS)
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val function = functionS
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def matches(name: String): Boolean = names.exists(n => name == n || name == n.split("\\.").last)
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val calls = {
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val all = cpg.call.filter(c => matches(c.name)).l
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if (function.isEmpty) all else all.filter(_.method.name == function)
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}
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val rows = calls.map { call =>
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// Joern indexes the receiver at 0, positional arguments from 1, and NAMED arguments at -1. A setting is
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// configured overwhelmingly by keyword (`origins="*"`, `secure=False`), so filtering `argumentIndexGt(0)`
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// -- correct when counting arity for the taint shape test -- drops exactly the arguments that matter here
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// and every keyword-configured setting reads as "computed".
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val args = call.argument.filter(_.argumentIndex != 0).l
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ujson.Obj(
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"setting" -> call.code.take(200),
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"line" -> call.lineNumber.getOrElse(-1).toString,
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"method" -> call.method.name,
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"args" -> ujson.Arr(args.map(a => ujson.Str(a.code.take(80))): _*),
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// A keyword argument (`origins = "*"`) is an assignment-shaped node, so `isLiteral` is false on the
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// argument itself and the literal sits inside it. Collect literals from the argument's SUBTREE, or
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// every keyword-configured setting reads as "computed" and nothing is ever evaluated.
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"literalArgs" -> ujson.Arr(args.flatMap(a => a.ast.isLiteral.code.l).distinct.map(c => ujson.Str(c.take(80))): _*)
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)
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}
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rows
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}
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println("---OUSAST-CPG-BEGIN---")
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if (requests.nonEmpty) {
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val parsed = ujson.read(requests).obj
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val answers = parsed.map { case (id, req) =>
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def field(name: String): String = req.obj.get(name).map(_.str).getOrElse("")
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id -> ujson.Arr(rowsFor(field("settings"), field("function")): _*)
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}
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println(ujson.write(ujson.Obj.from(answers)))
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} else {
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println(ujson.write(ujson.Arr(rowsFor(settings, function): _*)))
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}
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println("---OUSAST-CPG-END---")
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}
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