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Sprint projectSep 12, 2026Sudbury, Ontario, Canada

An iota of signal in a flood of noise: a stateful detector improves synthetic intrusion detection from 13% to 92%

Kevin Vaillancourt

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: An iota of signal in a flood of noise: a stateful detector improves synthetic intrusion detection from 13% to 92%

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Events viewed in isolation do not carry enough signal to cross the threshold into a security event; the accumulation of events does. The detector averages an entity’s past events and scores the average beside the current event. On synthetic campaigns calibrated to the timing and phase structure of Hugging Face’s 108-hour incident, with false alarms capped at 5%, detection within 120 hours rises from 13% without memory to 92% with it. Controls show the advantage depends on ordered evidence staying attached to the same entity; breaking that removes most of the gain. The evaluation uses four benign entities per attacker; an earlier attackers-only result of 59% was an entity-age artifact and was replaced. Rdet, the share of predictive information attributable to history rather than the current event, is a diagnostic for whether history holds exploitable signal. These rates are properties of the synthetic generator, not measurements of Hugging Face telemetry

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  1. The problem is well-chosen and timely, but CUSUM ties the detector at both windows, so the contribution is closer to "stateful beats stateless" than a new method. Table 4 on entity keying is the genuinely novel piece and deserves to be the headline.

    Calibration is honest, with the full detection/false-alarm curve rather than a single favourable point. The repo backs every table with a named script. Capped by being entirely synthetic on a generator the author wrote.

    Scope discipline is unusually good; the abstract's number needs the per-event-signal caveat that Table 5 shows is essential; the Discussion is thin; limitations are restated four times in near-identical wording.

  2. This project provides a careful synthetic evaluation of a simple but important containment idea: weak signals that are individually insufficient may become useful when accumulated over time for the same entity. The strongest aspect is methodological self-correction. The author discovered that the original 59% headline was driven by entity age rather than meaningful history, replaced the attackers-only evaluation with a setup containing four benign entities per attacker, and then added controls that test whether the gain depends on temporal order and persistent identity linkage. Under that corrected synthetic protocol, memory improves 120-hour detection from 13% to 92% at a 5% false-alarm rate, while the benefit falls sharply when histories are wiped, assigned to another entity, or spread across rotating identities. The main limitation is that these rates are properties of a custom synthetic generator calibrated to incident timing and phase structure, not evidence from real intrusion telemetry; CUSUM also performs about as well under the reported setup. The most valuable next step is evaluation on real or more realistic multi-entity security logs, using much more benign-heavy populations, adversarial key rotation, calibrated alert-volume costs, and comparisons with modern sequence and graph-based baselines.

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Cite this project

@misc{vaillancourt2026iota,
  title = {{An iota of signal in a flood of noise: a stateful detector improves synthetic intrusion detection from 13\% to 92\%}},
  author = {Kevin Vaillancourt},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/an-iota-of-signal-in-a-flood-of-noise-a-stateful-detector-improves-synthetic-intrusion-detection-from-13-to-92-e3wk}},
  url = {https://apartresearch.com/sprints/projects/an-iota-of-signal-in-a-flood-of-noise-a-stateful-detector-improves-synthetic-intrusion-detection-from-13-to-92-e3wk}
}

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