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* refactor(analysis): centralize resource budgets and recovery facts * feat(analysis): expose ASAR and Ghidra runtime admission controls * feat(artifacts): expose reader admission and preserve limited recognition * feat(javascript): expose recoverable semantic precision budgets * feat(web): add recoverable source-map budgets and compact retained views * feat(web): make historical capture decoding budgets recoverable * fix(desktop): enforce selected view policies across capture and export * feat(runtime): make Frida and LLDB retention budgets selectable * feat(native): expose diagnostic budgets and preserve exhaustion causes * feat(managed): expose recoverable snapshot and representation budgets * feat(metadata): make Go and Rust inspection budgets recoverable * feat(wasm): expose representation and producer admissions * feat(evm): expose per-call worker resource budgets * feat(android): make resource and string-pool omissions recoverable * feat(producers): expose command and recorded-capture budgets * docs(analysis): record recovery contracts and integrated validation * fix(docs): link calibration oracle from published verification pages * fix(docs): restore desktop task anchors and receipt links * test(analysis): align fixtures with selectable budget contracts * fix(analysis): remove source-location projector dependency cycle * test(analysis): refresh budget recovery and verifier regressions * test(analysis): preserve format and publication recovery expectations * test(windows): align conformance with owned runtime admission * fix(desktop): preserve selected alias kinds in exported state * test(analysis): align provider fixtures with recoverable budgets * test(desktop): validate emitted alias metadata structurally * fix(ghidra): classify bounded Windows endpoint refusals * test(cli): assert selectable artifact admission recovery * fix(cli): preserve capture provenance in environment builds
60 lines
2.3 KiB
TypeScript
60 lines
2.3 KiB
TypeScript
import { projectCliAnalysisResult } from "./projectCliAnalysisResult.js";
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import { z } from "incur";
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import type { DirectAnalysis } from "../composition/directAnalysis.js";
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import { CLI_COMMANDS } from "../cliCommandNames.js";
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import { parseCliJsonInput } from "../cliJsonInput.js";
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import { logCliCommand } from "../cliLogging.js";
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import { projectAnalysisError } from "../domain/analysisErrorProjection.js";
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import { analysisInputErrorFromIssues } from "../domain/inputIssueProjection.js";
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import { jsonValueSchema } from "../domain/jsonValue.js";
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import { localPathStringSchema } from "../domain/localPath.js";
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import { nativeCallObservationInputSchema } from "../domain/native/nativeCallObservation.js";
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import type { Logger } from "pino";
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import type { CliInstance } from "./types.js";
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const OPERATION = "observe_native_calls";
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/** `observe-native-calls <path> <input-json>`: the MCP input object as JSON. */
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export const registerNativeCallCommands = (
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cli: CliInstance,
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logger: Logger,
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runProviderAnalysis: DirectAnalysis["runProviderAnalysis"],
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): void => {
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cli.command(CLI_COMMANDS.observeNativeCalls, {
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description:
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"Launch a Mach-O under LLDB and record entries into selected functions or Objective-C methods",
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args: z.object({
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path: localPathStringSchema.describe("Mach-O or app path"),
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inputJson: z
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.string()
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.describe(
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"Inline JSON or a JSON file path: breakpoints, arguments, environment, duration_ms, max_events, argument_registers, backtrace_frames, capture_limits",
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),
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}),
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run: ({ args }) =>
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logCliCommand(logger, CLI_COMMANDS.observeNativeCalls, async () => {
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const input = await parseCliJsonInput(args.inputJson, OPERATION);
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if (!input.ok) return input.error;
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const parsed = nativeCallObservationInputSchema.safeParse(input.value);
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if (!parsed.success)
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return {
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error: "Analysis failed",
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...projectAnalysisError(
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analysisInputErrorFromIssues(
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OPERATION,
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parsed.error.issues,
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input.value,
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),
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),
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};
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return runProviderAnalysis(
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args.path,
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OPERATION,
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z.record(z.string(), jsonValueSchema).parse(parsed.data),
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logger,
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).then(projectCliAnalysisResult);
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}),
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});
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};
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