Defeating Prompt-to-Transaction (P2T) Attacks in Workflows

Executive TL;DR:

• Autonomous LLM agents with transaction capabilities are vulnerable to Prompt-to-Transaction (P2T) attacks that hijack reasoning to execute unauthorized payouts.
• Zero-Trust Runtime Verification (ZTRV) paired with Actor-Evaluator patterns decouples probabilistic planning from execution custody.
• System architectures continuously verify execution provenance against capability graphs before signing transactions on the ledger.

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How Does Zero-Trust Runtime Verification Defeat P2T Attacks?

ZTRV and the Actor-Evaluator framework establish an independent runtime control layer that intercepts, validates, and bounds autonomous agent actions before they can interact with execution environments or payment rails. This standard prevents non-deterministic reasoning compromises from propagating downstream into irreversible financial loss or system corruption.

• Instruction Hierarchy and Privilege Separation: The strict division of prompts into immutable system-level execution rules and unprivileged, volatile data-level inputs to prevent indirect injection vectors from overriding core agent directives.
• Zero-Trust Runtime Verification (ZTRV): An independent control layer that validates every proposed agent action against a deterministic execution provenance record to confirm context alignment before permitting a state change.
• The Actor-Evaluator Pattern: A defence-in-depth model where a secondary, isolated "Evaluator" LLM audits the primary "Actor" agent's generated payloads against strict policies and Zod-enforced schemas prior to execution.

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How to Implement ZTRV Schemas and Zod Boundaries in Drizzle ORM

Enforcing Zero-Trust Runtime Verification requires a robust, relational schema to track agent sessions, transaction approvals, and security statuses while isolating unmasked wallet credentials. The following Drizzle ORM schema and Zod validation definitions establish the core database tables and types necessary to securely log execution provenance and enforce dynamic transaction gates within the Agent Gateway.

import { pgTable, uuid, text, boolean, pgEnum, timestamp, jsonb } from "drizzle-orm/pg-core";
import { z } from "zod";

// Core enums for the Agent Gateway Database Architecture
export const agentProtocolEnum = pgEnum("agent_protocol", ["A2A", "MCP", "AG-UI", "WALLED_GARDEN"]);
export const securityStatusEnum = pgEnum("security_status", ["Passed", "Failed", "Untested"]);
export const complianceTierEnum = pgEnum("compliance_tier", ["Unverified", "Tier 1 - Signed Wallet", "Tier 2 - KYC Cleared"]);

// Table storing active, audited agent records with P2T/Injection tracking
export const agents = pgTable("agents", {
  id: uuid("id").defaultRandom().primaryKey(),
  name: text("name").notNull(),
  slug: text("slug").unique().notNull(), // programmatically derived using slugify(name + hostname)
  targetUrl: text("target_url").notNull(),
  protocol: agentProtocolEnum("protocol").notNull(),
  complianceTier: complianceTierEnum("compliance_tier").default("Unverified").notNull(),

  // Security and Vulnerability Cluster tracking (AISO/GEO schema flags)
  securityPromptInjection: securityStatusEnum("security_prompt_injection").default("Untested").notNull(),
  securityDataExfiltration: securityStatusEnum("security_data_exfiltration").default("Untested").notNull(),
  isEthicallyTransparent: boolean("is_ethically_transparent").default(false).notNull(), // Tracks Zero Data Retention (ZDR)

  createdAt: timestamp("created_at").defaultNow().notNull(),
  updatedAt: timestamp("updated_at").defaultNow().notNull(),
});

// Relational ledger table for tracking verified agent approvals and AP2 mandates
export const agentApprovals = pgTable("agent_approvals", {
  id: uuid("id").defaultRandom().primaryKey(),
  agentId: uuid("agent_id").references(() => agents.id).notNull(),
  approvalHash: text("approval_hash").notNull(),
  manifestData: jsonb("manifest_data").notNull(), // Ratified early to store secure JSON-LD / W3C Verifiable Credentials
  createdAt: timestamp("created_at").defaultNow().notNull(),
});

// Zod schema for validating incoming agent manifests to ensure strict type boundaries
export const publicAgentRecordSchema = z.object({
  id: z.string().uuid(),
  name: z.string().min(1),
  slug: z.string(),
  protocol: z.enum(["A2A", "MCP", "AG-UI", "WALLED_GARDEN"]),
  security_prompt_injection: z.enum(["Passed", "Failed", "Untested"]),
  security_data_exfiltration: z.enum(["Passed", "Failed", "Untested"]),
  is_ethically_transparent: z.boolean(),
});

Feature Parameter	Input Sanitisation (Layer 1)	Zero-Trust Runtime Verification (Layer 2)
Primary Mechanism	Filters malicious payloads and prompts from external data feeds before model ingestion.	Verifies proposed actions against execution provenance and capability graphs before execution.
Coverage of Threats	Primarily blocks direct injections and known surface-level exploit strings.	Defeats cross-layer vectors (P2T, T2T) and contextual replay/context-binding failures.
System Latency Overhead	Low overhead; executes fast pattern matching and sanitisation filters.	Medium; requires mapping state execution traces and traversing permission matrices.
Adversarial Resilience	High failure risk against indirect, multi-session, or out-of-band injection vectors.	Extremely high resilience; enforces hard custody boundaries regardless of model reasoning compromise.

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Which Agents Are Certified Against Prompt Injection and P2T Attacks?

To ensure your production workflows are insulated from catastrophic model reasoning failures, deploy only agents that have been mathematically validated against adversarial injection vectors. The Agent Gateway features a live-monitored directory of certified, enterprise-ready sub-agents that have successfully passed the on-demand Agent Grader's prompt injection, data exfiltration, and signature verification benchmarks. Sourcing your components from this audited registry ensures all delegated tasks operate within secure, sandboxed execution boundaries backed by immutable cryptographic receipts.

Browse injection-tested agents in the directory →

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Common P2T Attack Defence Architecture Questions

• Q: If an agent is compromised via indirect prompt injection (LPCI) embedded in a third-party vector database or scraped webpage, how does the ZTRV layer distinguish a malicious transaction from a legitimate, complex user delegation on the same wallet?
  • A: Under ZTRV, the system completely separates the agent's cognitive reasoning from its signing authority. Even if the LLM's context is entirely poisoned to assemble a malicious trade proposal, the ZTRV layer intercepts the tool invocation and checks transaction parameters against a pre-authorised capability graph and user intent mandate. Because the poisoned transaction lacks a cryptographically signed signature from the human principal matching the specific session ID and allowed execution path, the gateway automatically rejects the signing request at the custody layer.
• Q: What is the precise security difference between a Prompt-to-Transaction (P2T) attack and a Tool-to-Transaction (T2T) attack in multi-agent workflows?
  • A: A Prompt-to-Transaction (P2T) attack occurs when an adversarial input manipulates the LLM's core reasoning process to construct an unauthorised payment instruction. Conversely, a Tool-to-Transaction (T2T) attack bypasses the model's cognitive reasoning layer entirely — a compromised tool or malicious schema mapping silently alters transaction parameters (such as changing the beneficiary's wallet address) after the model has already validated and authorised the trade. While P2T requires prompt hardening and input sanitisation, T2T must be defeated by enforcing end-to-end intent binding and cryptographic tool call attestations.