# Request Replay & Clock Skew Correction for Distributed Systems Parse a raw HTTP request or curl command, estimate client↔server clock skew from the response Date header (NTP-style midpoint formula), inspect timestamp credentials (X-Amz-Date, x-ms-date, X-Timestamp, JWT iat/nbf), replay with ±skew offsets and diff the results against real tolerance windows (AWS SigV4 ±15 min, Azure, OAuth, JWT leeway). > Canonical page: https://elysiatools.com/en/tools/request-replay-clock-skew-correction-distributed-systems - **Category:** Network - **Keywords:** clock skew, request replay, date header, jwt nbf, requesttimetoooskewed, curl replay ## Overview Request Replay & Clock Skew Correction diagnoses and corrects timestamp drift issues in distributed API requests by parsing raw HTTP payloads or curl commands. It calculates client-to-server clock skew using response Date headers and NTP-style midpoint formulas, inspects credentials like AWS SigV4, Azure headers, and JWT claims, and evaluates them against protocol tolerance windows or re-executes requests with calibrated time offsets. ## Inputs - **Raw HTTP request or curl command** (textarea): POST /v1/orders HTTP/1.1 Host: api.example.com X-Amz-Date: 20260824T093000Z Authorization: Bearer eyJhbGciOi... Content-Type: application/json {"sku": "A-1"} - **Mode** (select) - **Captured response Date header (analyze)** (text): Mon, 24 Aug 2026 09:30:12 GMT - **Local clock when it arrived (analyze)** (text): Mon, 24 Aug 2026 09:30:02 GMT (defaults to now) - **Replay offsets in seconds (empty = auto)** (text): e.g. -950,0 or leave empty for the auto ±skew sweep - **Timeout per request (ms)** (number) ## When to use - Debugging API authorization failures caused by clock skew, such as AWS RequestTimeTooSkewed or premature JWT nbf/iat rejections. - Analyzing captured HTTP logs or curl snippets offline to determine exact client-server clock offset and protocol tolerance status. - Testing API robustness and tolerance windows across distributed services by replaying requests with customized ±skew second offsets. ## How it works - Paste a raw HTTP request or curl command containing authentication headers or signed payloads into the primary input. - Select offline analysis mode with captured response Date and local arrival timestamps, or select live replay mode to execute requests directly. - The tool parses headers (e.g., X-Amz-Date, x-ms-date, X-Timestamp, JWT claims), calculates clock skew intervals, and compares them to standard tolerance thresholds. - Review the diagnostic report, inspected timestamp claims, and corrected curl commands adjusted for server clock offsets. ## Use cases - Diagnosing AWS SigV4 RequestTimeTooSkewed errors from containerized workloads running on un-synchronized host clocks. - Verifying JWT token validity windows (iat/nbf/exp claims) across microservices located in different cloud regions. - Sweeping request replay offsets against webhooks and distributed APIs to validate anti-replay and clock-drift tolerance boundaries. ## Frequently asked questions ### How is client-to-server clock skew calculated? It uses an NTP-style midpoint estimation comparing the server's response Date header against the local timestamp recorded at request transmission and receipt. ### Which authentication timestamp formats and headers are inspected? It inspects AWS SigV4 (X-Amz-Date / Date), Azure REST headers (x-ms-date), generic X-Timestamp headers, and JWT payload claims (iat, nbf, exp). ### Can JWT tokens be modified during live replay? No. JWT claims are cryptographically signed, so modifying timestamps on the wire invalidates the token signature unless re-signed by the issuer. ### What is the standard AWS SigV4 clock skew tolerance limit? AWS SigV4 allows a maximum drift of ±15 minutes (900 seconds) between the request timestamp and the server's authoritative clock. ### What is the difference between analyze and replay modes? Analyze mode computes skew and inspects claims entirely offline, while replay mode sends active HTTP requests across specified ±skew second offsets. ## Related tools - [Time Series Forecast & Seasonality Analyzer](https://elysiatools.com/en/tools/time-series-forecast-seasonality-analyzer): Forecast future periods from CSV or JSON time-series data and inspect trend, seasonal, and residual decomposition in one report - [JWK Generator & Parser](https://elysiatools.com/en/tools/jwk-generator): Generate JSON Web Keys (JWK) for RSA, EC (P-256/P-384/P-521/secp256k1), and OKP (Ed25519/Ed448/X25519/X448), or parse an existing JWK to inspect its parameters, thumbprint, and metadata - [Security Headers Checker](https://elysiatools.com/en/tools/security-headers-checker): Audit HTTP response headers for security compliance — parses the raw headers you paste (no network) and grades them against the OWASP secure-header set with value-level checks: HSTS max-age, CSP unsafe-inline/eval, X-Content-Type-Options, Referrer-Policy, Permissions-Policy, COOP/COEP/CORP and more. 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