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The property test asserted an absolute 250ms ceiling on sanitizeErrorMessage() for adversarial inputs. That ceiling had no margin over the pipeline's real fixed cost (3x redact + 2x normalize passes added by #12506), so it failed on cost under any machine load, not on backtracking. Replace it with a check that the sanitizer's cost does not scale with input length beyond a generous noise allowance, which is what a bounded-backtracking guarantee actually claims; keep a coarse absolute hang ceiling as a backstop.
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changelog.d/fixes/13907-redos-guard-cost.md
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changelog.d/fixes/13907-redos-guard-cost.md
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- fix(tests): replace the flaky 250ms wall-clock ReDoS guard in `sanitizeErrorMessage`'s property test with a deterministic cost-scaling check, so the test proves bounded-backtracking instead of failing on machine load (#13907)
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@@ -30,13 +30,55 @@ test("sanitizeErrorMessage never leaks a file path / stack frame", () => {
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);
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});
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test("sanitizeErrorMessage terminates on long adversarial input (ReDoS guard)", () => {
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// This guards against ALGORITHMIC (super-linear/exponential) blowup on adversarial
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// content — e.g. catastrophic regex backtracking — not raw throughput. Sanitization
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// has a fixed per-call cost (layered redact/normalize passes over a bounded, truncated
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// buffer) that does not scale with input length past the truncation point, so a tight
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// absolute wall-clock bound is inherently flaky under CI/machine load (it has no margin
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// over that fixed cost, and the same load inflates every measurement here uniformly).
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// Instead we assert the cost does NOT blow up with input size: a baseline taken on a
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// small input is compared, with a generous multiplicative+additive allowance for
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// scheduler/GC noise, against inputs from 1,000 to 20,000 chars. A real ReDoS
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// (superlinear/exponential backtracking) grows orders of magnitude faster than this
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// allowance regardless of machine load; ordinary fixed-cost regex work never gets close.
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function timeSanitize(input: string): number {
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const start = process.hrtime.bigint();
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sanitizeErrorMessage(input);
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return Number(process.hrtime.bigint() - start) / 1e6;
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}
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function buildAdversarialInput(len: number): string {
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return "a".repeat(len) + "@" + "b".repeat(len) + ".com " + "1".repeat(len);
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}
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function medianOf(samples: number[]): number {
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const sorted = [...samples].sort((a, b) => a - b);
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return sorted[Math.floor(sorted.length / 2)];
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}
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test("sanitizeErrorMessage cost does not scale with adversarial input size (ReDoS guard)", () => {
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// Warm up the JIT before measuring so the baseline isn't inflated by cold-start cost.
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for (let i = 0; i < 3; i += 1) timeSanitize(buildAdversarialInput(300));
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// Baseline: median of several small-input runs, well under any truncation boundary.
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const baselineMs = Math.max(
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medianOf([1, 2, 3].map(() => timeSanitize(buildAdversarialInput(300)))),
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1
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);
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// Coarse absolute backstop only — "did it hang forever" — never the primary assertion.
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const HANG_CEILING_MS = 5000;
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// Generous allowance for scheduler/GC noise under a loaded CI machine — calibrated well
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// above observed variance (baseline vs. worst-case adversarial run stayed under ~30x
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// even on a heavily loaded box) so only genuine algorithmic blowup can trip it.
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const NOISE_TOLERANT_CEILING_MS = baselineMs * 100 + 1000;
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fc.assert(
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fc.property(fc.integer({ min: 1000, max: 20000 }), (len) => {
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const start = process.hrtime.bigint();
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sanitizeErrorMessage("a".repeat(len) + "@" + "b".repeat(len) + ".com " + "1".repeat(len));
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const ms = Number(process.hrtime.bigint() - start) / 1e6;
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assert.ok(ms < 250, `too slow: ${ms}ms for len=${len}`);
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const ms = timeSanitize(buildAdversarialInput(len));
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assert.ok(ms < HANG_CEILING_MS, `hung: ${ms}ms for len=${len}`);
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assert.ok(
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ms < NOISE_TOLERANT_CEILING_MS,
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`cost scaled with input length (possible backtracking): ${ms}ms for len=${len} vs baseline ${baselineMs}ms`
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);
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})
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);
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});
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