mlsanityData to 14 Oct 2026

ElephantAgent: Contextual State Continuity in Agentic Systems

arXiv 2607.01919 ↗First posted 2 Jul 2026cs.AI cs.CRcited by 0

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

Agentic systems enhance their capabilities by invoking external tools and maintaining persistent memory. However, these external dependencies introduce novel attack surfaces. Recent tool and memory poisoning attacks show that maliciously crafted tool descriptors and poisoned memory can covertly bias agent behavior. These threats reflect a deeper issue: the lack of verifiable continuity in the agent's contextual state for planning and execution. We present ElephantAgent, a protocol that enforces Contextual State Continuity to defend against contextual state poisoning. Inspired by prior state-continuity mechanisms (e.g., Nimble), ElephantAgent extends this protection to the evolving contextual state of agentic systems. We define the contextual state as the bounded, security-critical subset of the agent's entire context (e.g., tool state and memory). Before processing each query, ElephantAgent recomputes the digest of the local contextual state and verifies it against the latest authorized digest. Using replicated trusted hardware, ElephantAgent maintains a linearizable ledger of authorized contextual state transitions and detects out-of-band state tampering. To handle in-band semantic abuse, ElephantAgent additionally provides Historical Traceability, enabling conditional post-hoc audit and recovery to a known-good prior state.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 6 of its 33 references that are in the map. First posted on arXiv 2 Jul 2026.

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6 of 33 references.

Closest ancestors · 2

Same direction, newest first

  1. 2026SuperLocalMemory: Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense Against Memory Poisoning17 Feb
  2. 2024AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases17 Jul

Other references · 4

  1. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,443
  2. 2024Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systemscited by 81
  3. 2024Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budgetcited by 5
  4. 2017Rollback and Forking Detection for Trusted Execution Environments using Lightweight Collective Memorycited by 2

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  1. 2026Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift
  2. 2026Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents
  3. 2026MemSecBench: Tracking Agent Memory Poisoning from Persistence to Consequence and Repair
  4. 2026AgentSys: Secure and Dynamic LLM Agents Through Explicit Hierarchical Memory Management
  5. 2026CONTINUITY: Security-Context Contracts for Composable LLM Agent Controls
  6. 2026Structurally Close, Temporally Distant: Measuring Security Exposure in Long-Horizon LLM Agents
  7. 2026Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems
  8. 2026SEAD: A State-Based Perspective on Attack and Defense in Tool-Using Agents