Forensic Trajectory Signatures for Agent Memory Poisoning Detection
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
Whether a trajectory-based detector can observe the retrieval provenance of an agent memory-poisoning attack is governed by one architectural variable: retrieval observability, whether the agent's memory access produces a logged tool call. We formalise this as a framework-agnostic retrieval-to-action provenance graph, classify published attack families by their position relative to it, measure the resulting coverage property against collected agent traces, and then falsify the detector's standalone deployment, reversing our own earlier recommendation to use the signature as a pre-filter ahead of recipient-metadata gating. Under exclusive tool-mediated payload access a retrieval-before-exfiltration event is structurally forced. Across eight non-overlapping zero-event control cells we observe 0 violations in 289 eligible successes over 87 scenario configurations. The invariant is empirically unbroken, but on the clustering unit no registered cell certifies the preregistered <=0.10 upper bound (per-cell bounds 0.10-0.35); a post-hoc pool of two control arms nominally clears it but is not credited. When the scaffold delivers the payload implicitly the signature disappears; we had read this as agents declining an available retrieval, but a follow-up shows it tracks store content instead, and that behavioural reading is withdrawn. The detector is then falsified for standalone use. Benign memory-grounded sends are trajectory-isomorphic: false-positive rate 24.7-57.6% on a 13-model factorial (N=4,160), positive predictive value <=3.85% at 1% attack prevalence, and a recipient-metadata gate flags 129/129 legitimate external emails. Retrieval-before-send is an attack precondition, not a maliciousness predicate; its cross-validated AUC also reflects membership of a 22-vector feature codebook, not generalisation. Companion to arXiv:2605.08442; we release the corpus and scoring code.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 18 of its 28 references that are in the map. First posted on arXiv 29 Jun 2026.
Builds on
18 of 28 references.
Closest ancestors · 15
Same direction, newest first
- 2026VIGIL: Runtime Enforcement of Behavioral Specifications in AI Agent Skills25 Jun
- 2026What If Prompt Injection Never Left? Rethinking Agent Security through Cross-Session Stored Prompt Injection3 Jun
- 2026From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents3 Jun
- 2026TRACES: Proactive Safety Auditing for Multi-Turn LLM Agents via Trajectory-State Modeling26 May
- 2026MemMorph: Tool Hijacking in LLM Agents via Memory Poisoning24 May
- 2026Hidden in Memory: Sleeper Memory Poisoning in LLM Agents14 May
- 2026MemLineage: Lineage-Guided Enforcement for LLM Agent Memory14 May
- 2026The Granularity Mismatch in Agent Security: Argument-Level Provenance Solves Enforcement and Isolates the LLM Reasoning Bottleneck11 May
- 2026Injection-Execution Dissociation: A Mechanistic Evaluation of Persistent Memory Attacks and Defenses in Stateful LLM Agents8 May
- 2026MEMSAD: Gradient-Coupled Anomaly Detection for Memory Poisoning in Retrieval-Augmented Agents5 May
- 2026Enforcing Benign Trajectories: A Behavioral Firewall for Structured-Workflow AI Agents29 Apr
- 2026Causality Laundering: Denial-Feedback Leakage in Tool-Calling LLM Agents5 Apr
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Other references · 3
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Citing papers per year: 2026: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
- 2026MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection
- 2026MemSecBench: Tracking Agent Memory Poisoning from Persistence to Consequence and Repair
- 2026The Trap of Trajectory: Towards Understanding and Mitigating Spurious Correlations in Agentic Memory
- 2026MemSentry: A Framework for Detecting Persistent Memory Poisoning in Agentic AI
- 2026Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
- 2026MemForm: Benchmarking Memory Formation Poisoning in LLM Agents
- 2026SMSR: Certified Defence Against Runtime Memory Poisoning in Persistent LLM Agent Systems
- 2026MAPLE-Guard: Memory-Aware Link Enforcement Against Memory-Link Poisoning in Multi-Agent Systems