Build blueprint
API Abuse Shape Detector
An edge middleware assigning abuse type, severity, and response tier to suspicious request sequences.
- Problem
- Rate limits catch volume but miss low-and-slow misuse that is semantically suspicious.
- Why Jev
- Risk decisions must be cheap enough for frequent invocation and return constrained actions.
- Architecture
- Aggregated request features → abuse Choice/Score → hard security rules → allow/challenge/block.
- Current alternative
- WAF signatures and expensive anomaly pipelines.
- Jev advantage
- Could add semantic judgment between static rules and heavyweight investigation.
- Unknowns
- Adversarial robustness and safe feature representation.
Why this confidence: Security value is high but unverified calibration makes autonomous blocking premature.
This is an authored hypothesis derived from the research corpus. Nothing here demonstrates product demand, or that Jev performs well on this particular workload. Run the validation experiment before building past the MVP.
Sources
Limitations
- Adversarial robustness and safe feature representation.
- This is a research hypothesis, not evidence of product demand or Jev performance in this workflow.
Supporting research
- Probabilistic predicate + deterministic action PlausibleJev supplies fuzzy predicates while TypeScript, policies, and workflows execute constrained actions.
- MAGI System on Jev ObservedAn open-source three-sage voting experiment inspired by Neon Genesis Evangelion.
- Cheap decision calls could make tens or hundreds of semantic judgments per event economical. SpeculativeThe product design follows from published pricing and parallel question primitives, not independent production evidence.
- Decision quorum PlausibleMultiple typed judgments are aggregated through voting or confidence-aware stopping.