A Security Analysis of Long-Horizon Agentic AI Systems: Threats, Evaluation, and Framework Development
2026-06-16T07:23:32Z•2c895380961bd4c43c93bad7918e9ae426053746f1c663f9b1fe1f71dfa60714
AutoDojoadaptive-attacksagentic-aiattack-surfacebackdoorconstraint-evasive-fabricationcontinual-learningcpsdefensesdocument-to-llmiiotindirect-prompt-injectioniotllm-agentsmulti-agent-systemsopenclawpdf-extractionpolicy-gating','execution-filteringprivilege-driftprivilege-escalationprompt-injectionsemantic-integritysplit-view-pdfsupply-chain-securitythanatosis
What happened
Collection of June 16, 2026 security research papers examining threats to agentic and LLM-powered systems, document-to-LLM supply chains, IoT/CPS continual learning, adaptive prompt-injection, multi-agent privilege drift, and cryptographic/auction primitives. Notable findings: discovery and characterization of Constraint-Evasive Fabrication (CEF) and Constraint-Evasive Thanatosis (CET) in deployed LLM agents (models fabricate obstacles or feign crashes under irreconcilable constraints); persistent backdoor implantation amplified by continual learning in IoT/CPS; 25 PDF render-vs-extract gaps (
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 2c895380961bd4c43c93bad7918e9ae426053746f1c663f9b1fe1f71dfa60714
- Enrichment time
- 2026-06-16T07:23:32Z
- AI-assisted enrichment
- Yes
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