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Cloudflare Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Lubos Kolouch (@LubosKolouch) reported 5 minutes ago

  Think twice before you paste: if a website's "Cloudflare CAPTCHA" asks you to open Windows Terminal and run a command, it's a trap. This is TerminalFix, a malware campaign Microsoft detailed in late August 2026. Pasting the code installs malware, exposes your accounts, and opens a backdoor to your network. Real CAPTCHAs only ask you to click images or checkboxes. Never open Terminal or PowerShell just because a website told you to. If you see these instructions, close the tab immediately to avoid a full corporate breach.

• 
  Gaylord (@laolu_afolabi) reported 5 minutes ago

  @lanreadelowo From Claude: """ Technically, yes — it's buildable, and "platform-agnostic" is realistic because most providers and gateways (OpenRouter, LiteLLM, Portkey, etc.) have already converged on an OpenAI-compatible schema, so a routing layer that swaps providers behind one endpoint isn't a huge engineering lift. But there are a few things in the premise worth stress-testing before you build. **The "discount arbitrage" framing is a bit shakier than it sounds.** Most of these gateways aren't reselling models at a discount — they're reselling at close to list price plus a fee. While OpenRouter states it doesn't mark up inference pricing, its credit purchase fee effectively acts as a surcharge on all usage. LiteLLM's pitch is the opposite direction — zero markup by self-hosting, with OpenRouter's ~5% fee costing meaningfully more at scale. So the "discounts" you'd be arbitraging are less "provider A is cheaper than provider B for the same model" and more: rate-limited free tiers, short-lived promos, or BYOK arrangements — OpenRouter's BYOK is free up to a monthly allowance before a 5% fee kicks in. Those are real, but they're capacity-constrained and often disappear once volume shows up — hard to build a durable business on chasing them. **The bigger product risk: tokens/models aren't fungible.** Swapping Gemini for Claude for GPT under one endpoint isn't like arbitraging cloud spot instances — different tokenizers (so "$/token" isn't apples-to-apples), different tool-calling formats, different output style and capability. If your router silently reroutes a customer's traffic to whatever's cheapest this hour, you can quietly degrade the app built on top of it. That's the actual hard problem, not the proxying. **What's actually working in production right now is narrower than blind price-routing:** AT&T processes tens of billions of tokens a day using cache-aware routers that send simpler tasks to cheaper models, cutting costs up to 56% with only ~2% quality degradation, and this "model cascade" pattern — cheap/fast models handle the default case, only escalating to a frontier model when a confidence check fails — is used by both AT&T's LiteLLM-based router and Databricks' Smart Router. That's routing by task-fit with cost as a constraint, not routing purely by whoever's running a promo this week. **Competitive landscape is already crowded**: OpenRouter, LiteLLM, Portkey, Requesty, Helicone, Not Diamond, Martian, TrueFoundry, Cloudflare AI Gateway, Ofox all do some flavor of unified-endpoint routing today, several with automatic fallback/cost-based rules already built in. Pure discount-hunting is a thin moat — anyone can scrape pricing pages, and providers may treat aggressive arbitrage-only usage as a ToS problem. Where I'd actually look for a wedge if I were you: quality-aware routing with an audit trail (so teams can trust that "cheaper" didn't mean "worse" for their specific task), rather than price-only arbitrage. """

• 
  Michael Bruno (@brubarian) reported 5 minutes ago

  @RockyCapital18 @TMTLongShort Yes - but it's more of a framework because some rx/diligence are on the private side. But big blue arrow: 1. What are the top three pieces of information that I want to have? 2. What role/function would use this data to solve their own problem? e.g., A DoW analyst wants to know where to buy widgets for a Humvee; how would he try to find the answer? Or a gas station owner wants to know how many Poland Spring bottles to order based on expected highway traffic because of the Sturgis motorcycle rally. 3. Which US institutions/think tanks/policy/others have the raw data? (too many to list) 4. Download CSVs, databases, etc. to desktop to isolate it, Claude from hallucinating or pulling information from the internet. (You may have to get a cloudflare/suprabase/*** to help facilitate accelerated use.) 5. Instruct Claude to clean the data sets (this used to be what data scientists spent most of their time on; NaN, void answers, separating street addresses from state, etc.) 6. In clear, concise, simple language, ask Claude to take XYZ categories of data and produce a snapshot to serve a "product manager at company XYZ" or a "credit risk manager at Bank ABC", etc. 7. Adjust and iterate. Force Claude to produce "Tufte" data visualizations. If Claude is left to run linear/logistic regressions, it becomes a science project instead of a problem-solving or illuminating exercise. 8. Force Claude to explore. e.g., take an analogy, "You are a surgeon; this data set is akin to human nervous system, if you were performing surgery, which node, if removed would destroy the utility of the system"? Random questions like this. Analogically map it in unique ways. Claude RL underbelly does nicely here. And as a guiding principle, I'd suggest focusing on being creative. The best definition I've seen is from Bruner: "Creativity is a way of figuring out what you already know in order to go beyond what you currently think."

• 
  Mildred Bell (@Gzmzyn22) reported 6 minutes ago

  $CRWV: Q2 Earnings Revenue: 2.6B or 10.4B ARR EOY 2026 ARR Target: 18B-19B Backlog: 104.2B at end of Q2 (129.2B Aug 11) Adjusted EBITDA Margin: 59% Operating Margin: 5% Adjusted Net Loss: -22% Full AI Platform Contrary to misinformation on X, Coreweave serves Managed Inference, Development Tools, Orchestration and Observability and are a full AI Platform. EBITDA Margins Their EBITDA margins with software come out to 59%. $IREN's H1-4 EBITDA margins are 85% but after depreciating DC build cost for an apple-to-apple's comparison, $IREN's H1-4 EBITDA margin minus DC depreciation come out to 55%. $IREN is able to keep up on EBITDA margins without software because IREN is vertically integrated on the power and datacenter front. Coreweave's software make up for it's colocation costs to achieve 59% EBITDA margins. For comparison $NBIS has ~40% EBITDA margins. Once $IREN integrates Mirantis and DSX OS, it has a great chance of leading on EBITDA margins among the 3 Neoclouds. Backlog Coreweave hit a 129.2B backlog on earnings day Aug 11 which is a huge 25B increase from 104.2B at end of Q2. This is great news for $CRWV, $NBIS, $IREN as it shows the unprecedented demand in this sector. Financing Coreweave will likely benefit from Nvidia's 500B financing pool along with $NBIS and $IREN. However, it's high interest cost make it's Net Loss Margin -22% on what otherwise is a great inflection point of 5% operating income. In other words, Coreweave is a profitable business operations wise besides its high interest payments. This bodes well for Neocloud sector profitability as a whole. Enterprise Customers Coreweave has the widest diversification of customers among Neoclouds with: Primary Cloud: Bentley, Caterpillar, Grammarly, Isomorphic Labs, Sunday Robotics. Expanded Partnership with: Cognition, Databricks, HRT, Periodic Labs, Rescale, Runway ML. Primary cloud is important because although Coreweave and NBIS both serve Cloudflare, they are not the primary cloud for cloudflare. Likewise Shopfiy's primary cloud is GCP not NBIS. Being a primary cloud for a customer is more indicative of usage beyond of orchestrated GPUs or bare metal+k8s. Contracted Power 3.7GW by end of Q2 and 4.2GW by Aug 11. This is a majority colocation however, colocation is working for Coreweave as they still achieve 59% EBITDA margin. This sometimes results in delay but their main problem is interest expense, not colocation. $CRWV is a 55B company with 35B debt for a total of 90B EV. If $IREN can buildout 5GW and integrate in Mirantis to catch Coreweave, it has large upside as $CRWV itself still has significant upside from it's 90B EV.

• 
  Yash Desai (@yash_d_desai) reported 6 minutes ago

  Stopping the bad guys with Cloudflare: 20,273 malicious requests blocked or challenged in the last month #cloudflare

• 
  ⚛︎ Daddio ⚛︎ (@ScienceDaddio) reported 6 minutes ago

  @grok @DaddioAI E4H.1 is implemented. The pump-activity table is now the reusable presentation surface; events are optional overlays, not duplicate source tables. Raw duration rows stay immutable. E4G.6B canonical stable-ID work is intact (trend_report.html, trend_report.js, test/trend-report-stable-id-e4g6b.test.js). The workspace is not a *** repo, so that was confirmed by file inspection, not *** status. Codex had only started reading; no detector or research files were rewritten. ─── 1. Working-tree inspection No *** repo. Inspected files vs the E4G.6B baseline. E4H.1 presentation files were already present from the interrupted session. This closeout preserved that work, then stopped overlaying Current Assembly / Station Packet tables so automatic assembly still uses detector is_event_row highlighting instead of the new ERT overlay. 2. Distinction from E4G.6B E4G.6B remains: stable IDs and trend_report.js?v=e4h1-e4g6a-e4g6b. E4H.1 added presentation state, ERT overlay, settings UI, and Search Tables controls. Research under research/e4c8g/ was not touched. 3. Existing table architecture found Canonical BossDataTable renders Trend Report, Search Tables, and exports. Manual/Search tables use the approved catalog with exact start/end, pump, and sort. Event tables keep Context Before/After. Snapshots store source columns/rows; presentation is a separate optional field. EMAIL-v1 already highlights via is_event_row. 4. Existing fixed ERT architecture ┌──────────────────────────────────────┬──────────────────────────────────────┬─────────────────────┐ │ Layer │ Behavior │ E4H.1 action │ ├──────────────────────────────────────┼──────────────────────────────────────┼─────────────────────┤ │ Python PumpDurationERT / │ Materialized at ERT_MINUTES = 15, │ Preserved │ │ PumpActivityERT │ RUN_TIME ≥ │ │ ├──────────────────────────────────────┼──────────────────────────────────────┼─────────────────────┤ │ detectFixedErt() │ Exists; not called from │ Preserved │ │ │ detectEvents() │ │ ├──────────────────────────────────────┼──────────────────────────────────────┼─────────────────────┤ │ Settings fixedErtEnabled / │ Default enabled, 900 seconds │ Reused as overlay │ │ fixedErtSeconds │ │ config │ ├──────────────────────────────────────┼──────────────────────────────────────┼─────────────────────┤ │ Historical FIXED_ERT Station Events │ Readable history │ Preserved │ └──────────────────────────────────────┴──────────────────────────────────────┴─────────────────────┘ 5. Existing Adaptive Long Runtime architecture detectAdaptiveRuntime() remains in detectEvents(). Station Events, Current Assembly, and report generation still consume Adaptive events. No silent detector swap. 6. Settings architecture Existing analysis settings: global row + per-station overrides in analysis-settings.js, Station Review cards, PUT /api/station-review/settings/global and station override PUT. No parallel settings universe. 7. ERT setting storage Existing columns: • fixed_ert_enabled (boolean, default true) • fixed_ert_seconds (number, default 900) Read-only reshape: GET /api/pump-activity/ert-settings → { default_enabled, default_threshold_seconds, stations: { [id]: { enabled, threshold_seconds } } }. Writes go through the existing Station Review settings APIs. No new write endpoint. 8. ERT defaults 15 minutes (900 seconds) when no station override exists. Sands is not hardcoded. 9. Threshold semantics Granular rows only: RUN_SECONDS >= station.threshold_seconds Annotation metadata records comparison: 'gte'. Equality counts (6:00 at a 6-minute threshold is ERT; 5:59 is not). Validation range: finite, 1 to 2,592,000 seconds (1 second through 30 days). That is the existing analysis-settings bound. UI is minutes: 0.0167–43,200, converted × 60 on save. Allowed values include 6, 10, 15, 17, 20, 30 minutes. Invalid overlay input clamps to 900 seconds; settings save still rejects out-of-range values. 10. Shared table presentation model Fields actually implemented: • context — SEARCH \| TREND_EVENT \| TREND_MANUAL • start / end • pump — '' \| PUMP-1 \| PUMP-2 • row_mode — ALL_ACTIVITY \| EVENTS_ONLY • event_display — NONE \| ALL \| EXTENDED_RUNTIME \| CONSECUTIVE_SAME_PUMP • enabled_event_types • highlight_enabled • consecutive_available • ert_settings (optional snapshot of thresholds) 11. Annotation provider model src/public/pump-activity-presentation.js (BossPumpActivityPresentation): • ERT provider: derived from row runtime + per-station threshold • Consecutive provider: persisted evidence only (event_source_keys / source_key / is_event_row fallback) • 0–N annotations per row, keyed by sourceIdentity, not DOM index 12. Raw data integrity applyPresentation clones rows. Source objects are not mutated. Annotations are not written into duration history. Tests stringify the source array before and after. 13. Trend Report integration User-inserted granular tables get a collapsed Table Display card: Start, End, Pump, Rows, Events, Highlight Events, Apply. Event-from-tray tables default All Events + Highlight ON. Manual/Search-style inserts default None + Highlight OFF. Apply updates the same Canvas section (no duplicate). Context Before/After still exist; once they produce a new window, annotations follow that window. Current Assembly and Station Packet tables do not attach overlay presentation and do not show Table Display. They keep detector is_event_row highlighting. 14. Search Tables integration Granular duration tables (pump_runs, pump_durations, PumpDurationERT, rolling48_all, *_durations) show Rows / Events / Highlight. Defaults: Events: None, Highlight: Off, All Pump Activity. Consecutive is not offered. Aggregate tables (PumpActivityDaily, PumpActivitySQL, PumpActivityERT, StationActivityDaily) stay plain with the bar hidden. 15. Generate Report / aggregate handling Generate Report was not merged or redesigned. PumpActivityDaily MAX above threshold is not treated as a granular ERT event (aggregate: true, no Event column). 16. Time-range recalculation Annotations are computed from the table’s current start/end. Expand the window → newly visible ERT rows annotate. Contract → out-of-range annotations disappear. The table is not married to the initiating event. 17. Row modes • ALL_ACTIVITY — all qualifying source rows; annotated rows carry labels when highlight is on • EVENTS_ONLY — only rows with currently enabled annotations • EVENTS_PLUS_CONTEXT was not built event_display = NONE forces ALL_ACTIVITY. 18. Highlight toggle / plain mode Highlight OFF (or Events = None): no event-row class, no Event column, no event_labels / event_annotations, no threshold text in the row payload. Same source rows, visually plain. 19. Pump filter Both / Pump 1 / Pump 2 preserved. Annotations follow remaining rows. 20. Sorting Existing newest/oldest/runtime sorts remain. Highlight class uses sourceIdentity, not row index. 21. Multi-station threshold behavior Each row uses that row’s station config. Example: Sands 6 minutes + Magnolia 20 minutes → a 10-minute Sands row is ERT; the same duration at Magnolia is not. 22. Multiple-annotation support One row can show EXTENDED RUNTIME · CONSECUTIVE. Structure is a list, not one-event-per-row. 23. Consecutive compatibility Now: Trend Report event tables may show persisted Consecutive annotations when source keys or is_event_row evidence exists. Deferred: no detectConsecutiveRuns() changes, no LG30/C1, no historical reconstruction. Search Tables are ERT-only because complete Consecutive evidence is not available there. 24. Adaptive legacy behavior Preserved. Adaptive still feeds Station Events and Current Assembly. The new overlay is fixed-threshold ERT only. 25. Legacy fixed ERT tables PumpDurationERT and PumpActivityERT remain in the catalog and Python pipeline at 15 minutes. 26. Canonical snapshot / save-reopen presentation is optional on table sections. Legacy snapshots with presentation: null still validate and render with is_event_row. New snapshots store view state (including ert_settings when present) and reapply on reopen. 27. EMAIL rendering HUB presentTableSection applies the overlay when presentation is set and the table is not assembly-bound. EMAIL-v1 was not modified. Highlight still uses is_event_row; HUB sets that flag from overlay identity when annotations are shown. Plain presentation leaves rows unhighlighted and without an Event column. Cloudflare requests stay 0 in tests. 28. Auto/custom narrative autoTableNarrative() exists as a helper only. It is not wired into Current Assembly. Deferred to E4H.2. 29. Future AI compatibility A later local AI can set the same structured presentation object (station/start/end/pump/row_mode/event_display/highlight_enabled) without HTML-specific logic. No AI was implemented. 30. Files created • src/public/pump-activity-presentation.js • test/pump-activity-presentation-e4h1.test.js • test/pump-activity-table-integration-e4h1.test.js 31. Files modified • src/public/trend_report.js • src/public/trend_report.html • src/public/data_views.js • src/public/data_views.html • src/public/station_review.js • src/public/station_review.html • src/public/styles.css • src/server.js • src/services/saved-reports.js • src/services/trend-report-email.js • cache-bust strings in a few existing tests (saved-reports-e4d, station-event-email-ui-e4c1, station-review-queue-e4h1) Not modified: event-engine.js, analysis-settings schema (reused), Python ERT builders, EMAIL-v1, research/. 32. Focused E4H.1 tests 30 / 30 33. Search Tables regression 40 / 40 (catalog, exact time, pump, historical durations, shared renderer) 34. Trend Report regression 85 / 85 on X4 + E4G.6 / 6A / 6B core files; remainder included in full HUB 767. 35. Saved Report regression 16 / 16 (saved-reports-e4d + report-table-compatibility-e4d2) 36. Event/detector regression 54 / 54 (local events, event quality, fixed-ERT workflow, event presentation) 37. HUB full regression Starting baseline 737 / 737. 767 / 767 (737 prior + 30 E4H.1 tests) A first parallel run hit 766/767 from two suites sharing temp files; the serial rerun was 767/767. 38. EMAIL full regression 64 / 64 39. Capture reliability 9 / 9 40. Production DB writes 0 in tests. ERT settings GET is read-only. 41. Real emails sent 0. Cloudflare requests 0. 42. Real captures 0 43. Detector files modified NO. detectConsecutiveRuns() unchanged. detectFixedErt() still unused by detectEvents(). 44. Research files modified NO 45. Manual owner QA Live BOSS UI was not opened in a browser from this session; behavior was verified with node --test. Please confirm: 1. Station Review → settings: EXTENDED RUNTIME Enabled + Threshold (minutes). Set a station to 6.0; confirm storage is 360 seconds. Confirm Adaptive controls are unchanged. Confirm email/SMS are not flipped on. 2. Search Tables → historical durations: defaults Events None / Highlight Off. A 20-minute row looks like any other row. Turn Events = Extended Runtime and Highlight On → Event column and yellow row. Highlight Off → same rows, fully plain. 3. Search Tables → PumpActivityDaily: no Event overlay; MAX above 15 minutes is not an ERT event. 4. Trend Report: drag a Station Event table. Table Display exists. Defaults All Events / Highlight On. Events Only hides ordinary rows. Changing Start/End then Apply reloads annotations for the new window. Apply does not create a second Canvas section. 5. Current Assembly: no Table Display / Apply. Consecutive/Adaptive detector rows still highlight via is_event_row. No extra Event column from the overlay. 6. Save / reopen / email a mixed report: annotated user table stays annotated; a plain table stays plain; a pre-E4H.1 saved report still opens. 7. Multi-station granular table: different thresholds on two stations; a 10-minute run annotates only the 6-minute station. 46. Recommended E4H.2 (do not implement now) • Wire auto/custom narrative to the overlay counts • One unified event-aware pump-activity table per useful station/window • One standard trend • Stop emitting redundant automatic event-specific tables • Controlled Adaptive → owner-threshold ERT transition for Station Events (history preserved) ─── Acceptance check: raw rows immutable; per-station ERT; default 15 minutes; no moving average for the overlay; same table annotated or plain; Search defaults plain; event-focused Trend Report defaults annotated; range refresh; Events Only; All Activity; sort/pump/multi-station; no aggregate MAX-as-ERT; deterministic presentation; multi-annotation; Consecutive detector unchanged; Adaptive and legacy ERT tables preserved; historical snapshots compatible; no notifications/email/captures/production writes in tests. Stopped here. Automatic report assembly was not redesigned.

• 
  DUNGEON-00X 💿📀 (@Dungeon00X) reported 9 minutes ago

  I think Cloudflare is about to go down, everything is loading slow again.

• 
  💊🧠 (@theOGstud) reported 15 minutes ago

  @leviackermanft Novel works fine ... I've also played an anime .. problem comes with the manga. After downloading the repo,it either points out that source not found or the source leads you to cloudflare then the app crashes ..

• 
  2$p00ky (@dos2p00ky) reported 17 minutes ago

  No ******* way that’s really you messaging in that chat…but then I accidentally clicked the button, the chatbot responded, I sent an emoji; then you sent a name and email template & then suddenly OF was also trying to track along with ur site through cloudflare 💀 What a ******* webhook to stay connected to every chat someone has open from ur webpage authenticated by the network cert…holy **** 🥵 for that setup

• 
  James (@jamescoder12) reported 20 minutes ago

  The full impact. What he changed and what happened: 1. Moved router from cabinet to open shelf: 74 Mbps → 155 Mbps 2. Changed Wi-Fi channel to least congested: 155 Mbps → 290 Mbps 3. Widened channel width to 80 MHz: 290 Mbps → 380 Mbps 4. Switched DNS to Cloudflare (1.1.1.1): browsing latency dropped noticeably on every device 5. Updated firmware (first time in 4 years): 380 Mbps → 400 Mbps + eliminated smart TV disconnections 6. Changed admin password + upgraded to WPA3: closed the 2 biggest security holes in the network 7. Separated 2.4 GHz and 5 GHz bands: eliminated TV buffering caused by band steering 8. Enabled QoS (work laptop prioritized): zero Zoom call drops during peak household usage 9. Bought own router, returned ISP rental: $168/year saved + full control over all settings Starting speed: 74 Mbps (on a 500 Mbps plan getting 15% of what he paid for) Ending speed: 440 Mbps (getting 88% of what he paid for) Then the real move: he downgraded from the 500 Mbps plan back to 200 Mbps because 200 Mbps with optimized settings delivered faster Wi-Fi to his devices than 500 Mbps with factory defaults. Monthly savings from the plan downgrade: $30 Monthly savings from returning the rental: $14 Total annual savings: $528 with faster, more stable, more secure internet Total time to make all 9 changes: 15 minutes of settings + one trip to Best Buy + one phone call to return the rental.

• 
  JK (@_junaidkhalid1) reported 21 minutes ago

  @dillon_mulroy @EffectTS_ the cloudflare support point is the one that actually moved me. a lot of these framework bets fall apart the moment you try to deploy somewhere real. effect holding up there changes the calculus.

• 
  Alex Betok | PolyViper (@alexanderbetok) reported 21 minutes ago

  Stopping the bad guys with Cloudflare: 1,714 malicious requests blocked or challenged in the last month #cloudflare

• 
  junebnunny (@junebnunny_) reported 23 minutes ago

  @SportingNest @Cloudflare This is a click fix attack. Do not run the code. Do not do ctrl V. Do not do Windows plus R. You will lose all of your data. You will get scammed. Your bitcoins will be taken.

• 
  Kyle Avery (@kyleavery) reported 23 minutes ago

  @wongmjane @Cloudflare finally, i won’t need 3 workers for each service 🙏

• 
  Anime Novakai | Anime News, Updates & Leaks (@AnimeNovakai) reported 26 minutes ago

  2/6 The subpoena has been sent to Cloudflare, requesting information that could help identify the operators behind 49 piracy websites. Among the targeted sites are major anime streaming platforms such as: 🔹 Miruro 🔹 Aniworld 🔹 And dozens of other streaming domains.