AML.T0031Erode AI Model Integrityview on ATLAS ↗Adversary degrades model output quality over time so users lose confidence or downstream consumers act on incorrect predictions.
T33 · Helmwart ID · OWASP MAS Guide source
In a blockchain agent like ElizaOS on Solana, a chain reorganisation reverses previously confirmed transactions, leaving the agent acting on internal state that no longer matches the canonical chain.
ExtendsT8: Repudiation and Untraceability · base threat in OWASP v1.1 catalog
A major Solana blockchain reorganisation (“reorg”) invalidates previously confirmed transactions performed by ElizaOS agents (an open-source multi-agent operating system). This is not a direct attack on ElizaOS; it is an inherent infrastructure risk. However, if the agent framework does not handle reorgs gracefully, the invalidated transactions leave downstream agent state incorrect, compounding into financial losses or cascading failures in dependent workflows.
An ElizaOS agent executes a confirmed buy order on a decentralised exchange. The trade appears in several block confirmations. The agent updates its internal position ledger, signals a peer agent to proceed with a follow-on sell strategy, and the peer agent begins placing orders. A blockchain reorganisation then occurs and the original buy transaction is reversed: it no longer exists on the canonical chain. The agent’s internal ledger still shows the position as open; the follow-on sell strategy continues to execute against a position that no longer exists on-chain, resulting in failed transactions, incorrect balance state, and potential double-spend conditions.
Agents build multi-step workflows on the assumption of transaction finality. A reorg retroactively invalidates earlier steps without triggering any agent-layer error, because the original confirmation event was genuine at the time of emission. In a multi-agent deployment, the reorg propagates through agent-to-agent signals: the agent that received the now-invalid confirmation signals downstream agents, which take autonomous actions based on a world state that no longer exists. Without a reorg event subscription and reconciliation path, the inconsistency persists and compounds across the fleet until a human audit identifies the discrepancy. T35 (Manipulation of Proof of Sampling) is the adversarial complement: where T33 is an infrastructure-induced audit failure, T35 is an attacker-induced one.
A reorg leaves a specific audit fingerprint: the agent’s internal ledger records a position that no longer exists on the canonical chain, and downstream agents continue acting on signals derived from the now-invalid transaction.
slotChanged or blockNotification subscription emitting a slot rollback) that is not followed within 30 seconds by a reconciliation_started event in the agent’s own audit log: a missing-reconciliation alert triggered by the reorg event itself.triggering_tx_hash against the RPC node’s confirmed block index.AlreadyProcessed error returned by the Solana runtime in response to a transaction submission: instrument the submission layer to count and alert on any such response, as it indicates the agent is resubmitting a transaction whose prior version was reorged.T33 extends T8 Repudiation and Untraceability. Where T8 addresses an attacker altering or suppressing records to evade accountability, T33 addresses an infrastructure event, the blockchain reorg, that retroactively alters the confirmed record of agent actions. The outcome is the same: the audit trail no longer accurately reflects what happened, and the agent’s state diverges from ground truth.
The Agentic Top 10 (ASI01 through ASI10) is a separate practitioner-facing publication that maps onto the master Threats & Mitigations threat numbering. T33 is covered by the following Top 10 entries:
A single low-severity fault (a hallucinated value, a corrupted tool output, a poisoned memory entry) propagates across a network of agents that each build on the last agent's output, compounding into system-wide harm that is disproportionate to the original defect. ASI08 is about propagation and amplification, not the fault's origin; the initial trigger may itself be innocuous.
Source: OWASP Top 10 for Agentic Applications 2026 (Dec 2025) · the Top 10 is a compass into the master Threats & Mitigations taxonomy, not a replacement for it.
When T33 is present, these security design principles are the ones being violated or tested. Each links to the full principle; the mitigations below are how you restore them.
Auto-generated from the mitigation catalog: every mitigation whose coverage map includes T33, sorted by maturity tier (Tier 1 production-canonical first, then Tier 2, then Tier 3 research-stage).
An agent that has been compromised, poisoned, or gone rogue will, in most cases, behave differently from its established baseline. Anomaly isolation acts on that difference: when an agent's behaviour score crosses a configured threshold, it is quarantined automatically, credentials revoked, message-queue access cut, in-flight actions aborted. Manual revocation cannot match the speed that cascading multi-agent failures demand.
why it helps Blockchain reorg exploitation depends on an agent acting on unconfirmed transaction state before on-chain finality. Anomaly isolation detects agents that deviate from their expected transaction-confirmation behaviour and quarantines them before further on-chain actions are committed.
A blockchain transaction, once committed, cannot be undone. An agent that signs and broadcasts a transaction without an enforcement layer before it can exceed its authorised value, call a contract it was never provisioned to reach, or drain a wallet in a runaway loop, and by then the funds are gone. A transaction guard intercepts each proposed transaction before signing, checks it against value bounds, a contract allowlist, a gas or compute-unit limit, and a replay-protection nonce, and refuses to sign anything that falls outside declared policy.
why it helps Blockchain Reorganisation exploits the window between transaction broadcast and finality. Requiring N-block confirmation before treating a transaction as settled reduces the reorg exploitation window. The guard does not eliminate reorgs below the confirmation threshold, but it prevents the agent from acting on unconfirmed state.
The OWASP OWASP MAS Threat Modelling Guide v1.0 catalogues 1 named multi-agent variant of T33, anchored to specific MAESTRO layers. Each is a concrete attack pattern that emerges when this threat compounds across agents.
A chain reorganisation attack (T33) rewrites the on-chain audit trail; agents relying on the reorged state make irrecoverable decisions (T26: resource misallocation); the post-hoc audit (T8) is unreliable because the canonical record itself changed.
Source: OWASP MAS Threat Modelling Guide v1.0, §2 Overview of MAESTRO Framework — Extended Threat Scenarios + Cross-Layer table.
MITRE ATLAS catalogues adversary techniques against AI systems. Where this OWASP threat has an attacker-perspective counterpart, the ATLAS technique is shown below. That is what a red team would actually be doing on the wire. Use this for detection-signal anchoring, threat-hunting hypotheses, and IR runbooks. Source: mitre-atlas/atlas-data v5.6.0.
© 2026 The MITRE Corporation. ATLAS content is reproduced and distributed with the permission of The MITRE Corporation.
AML.T0031Erode AI Model Integrityview on ATLAS ↗Adversary degrades model output quality over time so users lose confidence or downstream consumers act on incorrect predictions.
AML.T0067LLM Trusted Output Components Manipulationview on ATLAS ↗Adversary manipulates the structured parts of an LLM response (citations, tool-call arguments, approved-action markup) that downstream systems treat as trusted.
Agentic angle: Structured outputs are exactly what agent frameworks parse to decide what to execute. Undermining the structure undermines every safety check downstream.
Adapted by Helmwart from the OWASP source(s) above underCC BY-SA 4.0(changes: normalized IDs, added MAESTRO-layer, agentic-factor, and mitigation mappings). This entry is licensed CC BY-SA 4.0.
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