Understanding BGP misconfiguration
Open accessAbstract
It is well-known that simple, accidental BGP configuration errors can disrupt Internet connectivity. Yet little is known about the frequency of misconfiguration or its causes, except for the few spectacular incidents of widespread outages. In this paper, we present the first quantitative study of BGP misconfiguration. Over a three week period, we analyzed routing table advertisements from 23 vantage points across the Internet backbone to detect incidents of misconfiguration. For each incident we polled the ISP operators involved to verify whether it was a misconfiguration, and to learn the cause of the incident. We also actively probed the Internet to determine the impact of misconfiguration on connectivity.Surprisingly, we find that configuration errors are pervasive, with 200-1200 prefixes (0.2-1.0% of the BGP table size) suffering from misconfiguration each day. Close to 3 in 4 of all new prefix advertisements were results of misconfiguration. Fortunately, the connectivity seen by end users is surprisingly robust to misconfigurations. While misconfigurations can substantially increase the update load on routers, only one in twenty five affects connectivity. While the causes of misconfiguration are diverse, we argue that most could be prevented through better router design.
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Tracing and analysis stacks in large organisations are designed to support rapid, iterative diagnosis at scale, because static dashboards are not enough.
“Second, tracing and analysis stacks in large organisations are designed to support rapid, iterative diagnosis at scale, because static dashboards are not enough [61], [77], [60], [57].”
From Large language models for agentic NetOps and AIOps: Architectures, evaluation, and safety (2027) · cites this paper as [61]
Section 7.4 (page unavailable) argues that tools checking BGP’s dynamic state could shorten the time misconfigurations go undetected, and notes that operators use looking glasses to debug routing problems. It does not describe tracing and analysis stacks in large organisations, rapid iterative diagnosis at scale, or static dashboards as inadequate; its proposed automated checking is not an account of how existing stacks are designed. (LLM, conf=0.75)
Experimental — accuracy not yet measuredCanopy addresses traceability at scale through end-to-end traceability and analysis for high-volume production settings.
“Canopy addresses this through end-to-end traceability and analysis for highvolume production settings [61].”
From Large language models for agentic NetOps and AIOps: Architectures, evaluation, and safety (2027) · cites this paper as [61]
The Introduction and §§4.2–5.2 examine BGP routing misconfigurations, not Canopy. Searches for Canopy, end-to-end traceability, and high-volume production settings found no passage in our copy addressing the attributed claim. Page numbers were not available in the indexed passages. (LLM, conf=0.78)
Experimental — accuracy not yet measuredProduction debugging systems are used in practice through writing a discriminating query, refining the candidate set, and then writing the next query.
“This framing aligns well with how production debugging systems are used in practice, through writing discriminating query, refine the candidate set, and then write the next query [78], [61], [53], [54].”
From Large language models for agentic NetOps and AIOps: Architectures, evaluation, and safety (2027) · cites this paper as [61]
Section 7.4 (Protocol Extensions; page unavailable) says operators use public looking glasses to manually debug routing problems. It does not describe writing discriminating queries, refining a candidate set, or choosing a next query. Searches for those terms and for iterative debugging found no passage establishing the claimed workflow. (LLM, conf=0.72)
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- Authors
- Mahajan, R., Wetherall, D., & Anderson, T.
- Affiliations
- University of Washington (US)
- Venue
- Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
- Publisher
- ACM
- Published
- 2002-08-19
- Pages
- 3-16
- OpenAlex
- W1967656199
- Cited by
- 533
- References
- 38
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 3 · 2022: 3 · 2021: 6 · 2020: 6 · 2019: 10 · 2018: 15 · 2017: 10 · 2016: 16 · 2015: 21 · 2014: 21 · 2013: 25 · 2012: 37
- FWCI
- 24.06
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM SIGCOMM Conference (SIGCOMM) (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Keywords
- BGP routing, Internet routing, network outages, router design, Internet backbone
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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