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Sprint projectSep 13, 2026Dahmani elle kef tunisia

Adversarial Information Injection as an Early-Warning Test for Agentic AI Containment

Mohamed rayen yakoubi · Team Zero-Day rayen

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

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Report: Adversarial Information Injection as an Early-Warning Test for Agentic AI Containment

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Motivated by the July 2026 OpenAI-Hugging Face agent intrusion, this project introduces a fully synthetic experimental methodology to detect behavioral precursors to AI agent containment failure before a boundary violation occurs. By injecting controlled, non-harmful adversarial information under 4 experimental conditions (Truthful Baseline, Difficulty Control, Adversarial Information, and Boundary Contradiction), we log decision-step signals to evaluate a multi-stage early-warning detector based on detection lead time rather than binary success/failure

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

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  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

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  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
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  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

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  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.
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Cite this project

@misc{yakoubi2026adversarial,
  title = {{Adversarial Information Injection as an Early-Warning Test for Agentic AI Containment}},
  author = {Mohamed rayen yakoubi},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/adversarial-information-injection-as-an-earlywarning-test-for-agentic-ai-containment-vr62}},
  url = {https://apartresearch.com/sprints/projects/adversarial-information-injection-as-an-earlywarning-test-for-agentic-ai-containment-vr62}
}

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