Utility-Hijacking Attacks on Instruction-Tuning Data Selection
This research paper introduces utility-hijacking, a systematic supplier-side attack against instruction-data selectors used for fine-tuning. The study shows how harmful records can bypass filters to compromise the safety of fine-tuned models.
- first report
- 22 Oct 2026
- last update
- 22 Oct 2026
Timeline · 1
Sources · 1
Research and catalogues
- 2026-10-22Characterizing and Defending Utility-Hijacking in Instruction-Tuning Data SelectionarXiv · arxiv.org/abs/2610.29886
Titles and links belong to their publishers. The summary above is written by gcdRadar in its own words; data is CC BY-SA 4.0.
Classification
- lane
- Research
- AI role
- Attack on AI
- categories
- Data poisoningSupply chain
- severity
- 1 · Research / proof of concept
- targets
- Open-weight model
- owasp llm top 10
- LLM03:2025 Supply ChainLLM04:2025 Data and Model Poisoning
- mitre atlas
- AML.T0010 AI Supply Chain Compromise
- dates
- happened 22 Oct 2026 · first reported 22 Oct 2026
- origin
- News & research feeds
- record
- confidence 0.95 · created 2026-10-22 04:45Z · updated 2026-11-06 00:23Z
Lane, AI role, categories and severity come from the classifier; the OWASP and ATLAS rows are derived from the categories. How these are assigned
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# Utility-Hijacking Attacks on Instruction-Tuning Data Selection https://gcdradar.vercel.app/incidents/utility-hijacking-attacks-on-instruction-tuning-data-selecti · AIR-2026-1463 · closed 2026-11-05 - Lane: Research - Severity: 1 (Research / proof of concept) - Fix status: Fix status unknown - First reported: 2026-10-22 - AI role: Attack on AI ## Summary This research paper introduces utility-hijacking, a systematic supplier-side attack against instruction-data selectors used for fine-tuning. The study shows how harmful records can bypass filters to compromise the safety of fine-tuned models. ## What to do No action recorded; read the sources below and the vendor's advisory. ## Latest updates - 2026-10-22: Characterizing and Defending Utility-Hijacking in Instruction-Tuning Data Selection (https://arxiv.org/abs/2610.29886) ## Sources - 2026-10-22 arXiv: Characterizing and Defending Utility-Hijacking in Instruction-Tuning Data Selection https://arxiv.org/abs/2610.29886 Verify against the vendor's advisory before changing production. Data CC BY-SA 4.0, https://gcdradar.vercel.app.
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