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Paper finds prompt injection can shift Jev's typed decisions, though rarely to the attacker's target

2026-09-26 · that day's edition · one of the five

Adaptive attacks using score feedback push fresh-validation success from 1.8 percent to 3.5 percent.

Quoted from arxiv.org on 2026-09-26: Malicious content shifts action probabilities but rarely causes Jev to select the… Quoted from arxiv.org, checked 2026-09-26. “ Malicious content shifts action probabilities but rarely causes Jev to select the attacker's target.” quoted from arxiv.org · checked 2026-09-26
arxiv.org, quoted / Decision Hijacking: Prompt Injection Attacks on Jev Typed Probabilistic Decisions · source · Quoted under the quotation exception; no licence granted

A paper posted to arXiv on 23 September 2026 tests prompt injection against Jev, a non-generative decision model, using 510 reconstructed InjecAgent cases. The authors report that malicious content shifts action probabilities but rarely causes Jev to select the attacker's target, and that adaptive attacks using score feedback raise fresh-validation success from 1.8% to 3.5%.

What this rests on

  1. The abstract, submitted 23 September 2026, states: 'We examine these effects in Jev, a non-generative decision model, using 510 reconstructed InjecAgent cases.'

    Decision Hijacking: Prompt Injection Attacks on Jev Typed Probabilistic Decisions · arXiv · 2026-09-23

  2. The abstract states: 'Malicious content shifts action probabilities but rarely causes Jev to select the attacker's target.'

    Decision Hijacking: Prompt Injection Attacks on Jev Typed Probabilistic Decisions · arXiv · 2026-09-23

  3. The abstract states: 'Adaptive attacks using score feedback double the mean highest attacker-target probability found during optimization, while success on fresh validation calls rises from 1.8% to 3.5%.'

    Decision Hijacking: Prompt Injection Attacks on Jev Typed Probabilistic Decisions · arXiv · 2026-09-23

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