Publication2025
In-Context Vulnerability Propagation in LLMs [Work In Progress Paper]
The record
- Type
- Publication
- Date
- 7 July 2025
- Level
- International — held abroad
- Journal
- Proceedings of ACM Symposium on Access Control Models and Technologies SACMAT
- Pages
- 169-174
- Published
- 7 July 2025
- DOI
- 10.1145/3734436.3734459
- Scopus ID
- 105033084647
- Authors
- 3
- Open access
- No
- Citations
- 1
- International co-authorship
- Yes
- Co-author countries
- IN, US
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Framework for evaluating vulnerability propagation in large language models addresses AI security and trustworthiness in code generation systems.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
16 Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
Assessment of security vulnerabilities and bias in AI-assisted development relates to responsible institutional use and governance of emerging technologies.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-4.4 Public safety, cybersecurity and national security
Cybersecurity analysis of AI systems and vulnerability detection mechanisms support institutional security and risk management capabilities.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “In-Context Vulnerability Propagation in LLMs [Work In Progress Paper]”. Kortex.