In the news
SEMA-Auto: Sighted and Efficient Multi-Turn Attack with Autonomy
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- SEMA-Auto is an autonomous multi-turn jailbreak attacker that reads victim model responses and terminates itself upon success without external evaluators.
- Why it matters
- Security researchers and AI safety engineers need to understand evolving attack methods against language models to improve defenses.
- Watch out
- The paper demonstrates high success rates against multiple models but does not detail defenses or mitigation strategies for practitioners.
- jailbreak
- eval
The patterns behind this
- Agentic Context Engineering (Evolving Playbook)
- Blast-Radius Containment & Autonomy Bounds
- Budget-Guarded Autonomy
Each one covers how the technique works, when it earns its cost, and where it breaks.
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