Mobius Injection exploits semantic closure in LLM agents to enable single-message AbO-DDoS attacks achieving up to 51x call amplification and 229x latency inflation.
Not what you’ve signed up for: Compromising real-world llm- integrated applications with indirect prompt injection
4 Pith papers cite this work. Polarity classification is still indexing.
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Multi-agent LLM frameworks can spread compromises across agent boundaries via insecure memory inheritance during subagent spawning.
ASPO combines multi-agent LLM proposals with deterministic enforcement in a MAPE-K loop to select conflict-free, resource-feasible security patterns for IoT, delivering 100% safety invariants and 21-23% tail latency/energy reductions on testbed workloads.
Obfuscated prompts exhibit latent embedding collapse onto clean prompt manifolds in BERT encoders, with minimal clean-obfuscated margin of 1.02 and elevated intra-class variance of 3.33 +/- 6.23 despite high detection performance.
citing papers explorer
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Can a Single Message Paralyze the AI Infrastructure? The Rise of AbO-DDoS Attacks through Targeted Mobius Injection
Mobius Injection exploits semantic closure in LLM agents to enable single-message AbO-DDoS attacks achieving up to 51x call amplification and 229x latency inflation.
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When Child Inherits: Modeling and Exploiting Subagent Spawn in Multi-Agent Networks
Multi-agent LLM frameworks can spread compromises across agent boundaries via insecure memory inheritance during subagent spawning.
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Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems
ASPO combines multi-agent LLM proposals with deterministic enforcement in a MAPE-K loop to select conflict-free, resource-feasible security patterns for IoT, delivering 100% safety invariants and 21-23% tail latency/energy reductions on testbed workloads.
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On the Geometric Limits of Transformer Defenses against Obfuscation Attacks: Latent Embedding Collapse & Performance Robustness Gap
Obfuscated prompts exhibit latent embedding collapse onto clean prompt manifolds in BERT encoders, with minimal clean-obfuscated margin of 1.02 and elevated intra-class variance of 3.33 +/- 6.23 despite high detection performance.