G

Threat Model

Threat Model

Overview#

This document describes the threat model for the Gao Internet infrastructure.

Because Gao Internet combines decentralized infrastructure, programmable identity, automated AI execution, and economic settlement mechanisms, multiple threat surfaces exist across different layers of the system.

The threat model is organized by attack domain and covers:

  • Identity and authority risks

  • AI execution risks

  • Payment system risks

  • Network layer risks

  • DePIN infrastructure risks

  • Governance risks

  • Operational risks

This document provides a framework for understanding potential risks and the mitigation mechanisms built into the system architecture.

Threat Model Scope#

The Gao Internet threat model considers adversarial actors who may attempt to:

  • Gain unauthorized access to identity-controlled resources

  • Manipulate economic systems or payment flows

  • Exploit infrastructure nodes

  • Misuse AI execution capabilities

  • Disrupt network operations

  • Capture governance mechanisms

Assumed Adversary Capabilities

Adversary Type

Assumed Capabilities

Malicious users

Social engineering, key compromise attempts

Compromised agents

Misconfigured or hijacked automation workflows

Dishonest infrastructure operators

Fake service delivery, performance falsification

External attackers

Network-level attacks, replay attempts

Coordinated adversarial networks

Governance manipulation, collusion attacks

The threat model assumes that attackers may possess advanced technical capabilities.

Identity and Authority Threats#

Domain Ownership Compromise

Attack: An adversary attempts to seize control of a Gao Domain identity by compromising the owner’s private key or executing an unauthorized domain transfer.

Potential impact: Full authority over domain-bound permissions, agents, and policy configurations.

Mitigation mechanisms:

  • User-controlled signing keys

  • Explicit domain authority verification at runtime

  • Policy enforcement before any domain-scoped execution

  • No infrastructure-level override mechanism exists

Residual risk: Key compromise through device theft, phishing, or social engineering. Users are responsible for private key security.

Privilege Escalation

Attack: A compromised agent or misconfigured policy attempts to execute actions beyond its assigned capability scope.

Potential impact: Unauthorized access to connectors, financial operations, or infrastructure resources.

Mitigation mechanisms:

  • Capability-based execution controls enforced at the Policy Gate

  • Policy hash validation before execution

  • Risk-tier gating that escalates high-risk actions to human approval

  • Agents cannot modify their own policy configurations

AI Execution Threats#

Agent Misuse

Attack: An AI agent is configured or manipulated to perform harmful operations including unauthorized financial transactions, destructive automation, or excessive infrastructure consumption.

Mitigation mechanisms:

  • Policy Gate validation for every planned action

  • Approval Center workflows for high-risk operations

  • Deterministic execution boundaries enforced by GAR

  • Agents operate only within domain-authorized scopes

Prompt Injection and Tool Abuse

Attack: Agents interacting with external services are exposed to malicious prompts or manipulated data designed to override agent behavior.

Examples:

  • Prompt injection through external web content

  • Malicious tool response payloads

  • Corrupted knowledge source injection

Mitigation mechanisms:

  • Tool permission gating through capability controls

  • External content classified as unverified until validated

  • Context isolation within sandbox execution environments

  • Restricted tool execution environments

Unbounded Execution Loops

Attack: Automation workflows unintentionally or deliberately generate infinite execution loops, consuming infrastructure resources without bound.

Mitigation mechanisms:

  • Bounded execution windows enforced by GAR

  • Runtime timeout enforcement

  • Execution state monitoring with automatic termination

  • Budget limits configurable through policy profiles

Payment Layer Threats#

Unauthorized Settlement Attempts

Attack: An adversary attempts to trigger payment settlement without proper user authorization.

Examples:

  • Forged transaction requests

  • Replay attacks on previously authorized payment instructions

Mitigation mechanisms:

  • User-signed transaction verification for all settlements

  • Canonical receipt validation

  • Replay protection mechanisms

  • In-flight execution windows are bounded

Settlement cannot occur without explicit cryptographic user authorization.

Economic Manipulation

Attack: Malicious actors attempt to manipulate infrastructure economic incentives or payment routing to extract unearned compensation.

Examples:

  • Artificial demand generation for fake service usage

  • Performance metric falsification

Mitigation mechanisms:

  • Receipt-based accounting with verifiable delivery

  • Performance verification systems

  • Service delivery validation before compensation

Network Layer Threats#

Routing Manipulation

Attack: An adversary attempts to manipulate message routing within the network through node impersonation or routing table poisoning.

Mitigation mechanisms:

  • Deterministic node selection algorithms

  • Node reputation scoring

  • Encrypted communication channels for all inter-node messaging

Denial of Service

Attack: An adversary attempts to overload infrastructure nodes or communication channels to disrupt service availability.

Mitigation mechanisms:

  • Rate limiting at network endpoints

  • Traffic prioritization mechanisms

  • Distributed infrastructure architecture that avoids single-point bottlenecks

DePIN Infrastructure Threats#

Malicious Node Operators

Attack: An infrastructure operator falsifies service delivery metrics or withholds resources while claiming compensation.

Mitigation mechanisms:

  • Performance verification systems with independent measurement

  • Node reputation scoring affecting routing priority

  • Service delivery validation before compensation release

Infrastructure Collusion

Attack: A coordinated group of nodes collude to manipulate infrastructure markets, routing decisions, or compensation mechanisms.

Mitigation mechanisms:

  • Distributed node participation with no single-operator dominance

  • Reputation weighting that considers historical performance

  • Performance-based routing that distributes demand across the network

Governance Threats#

Governance Capture

Attack: An adversary coordinates sufficient governance weight to modify protocol behavior in ways that benefit themselves at the expense of other participants.

Mitigation mechanisms:

  • Contribution-weighted governance rather than pure token-weighted voting

  • Time-locked governance changes with public observation periods

  • Bounded governance authority that cannot override core protocol invariants

Critical boundary: Governance cannot reassign domain ownership, reverse settlements, or access user assets — regardless of vote outcome.

Parameter Manipulation

Attack: A governance participant attempts to adjust protocol parameters in ways that undermine system integrity without technically violating explicit rules.

Mitigation mechanisms:

  • Parameter change bounds limiting adjustment magnitude

  • Transparent governance process with public documentation

  • Protocol guarantee enforcement that supersedes governance decisions

Operational Risks#

Infrastructure Instability

Infrastructure nodes may become unavailable due to hardware failures, network disruptions, or operator abandonment.

Mitigation: Distributed infrastructure architecture, dynamic routing mechanisms, service redundancy across multiple node operators.

Software Vulnerabilities

Software vulnerabilities may exist within components of the Gao Internet stack.

Mitigation: Open-source code review, security audits, responsible vulnerability disclosure program, semantic versioning with deprecation grace periods.

Residual Risk#

Despite the mitigation mechanisms described in this document, certain risks cannot be completely eliminated.

Residual risks include:

  • Unforeseen software vulnerabilities in new releases

  • External network disruptions beyond the protocol’s control

  • Regulatory changes affecting participant operations

  • Unpredictable market conditions affecting infrastructure economics

  • Zero-day attack vectors not anticipated at design time

Participants in the Gao Internet ecosystem must evaluate these risks independently.

Security Responsibility Model#

Security responsibilities are distributed among ecosystem participants.

Participant

Responsibility

Users and Organizations

Safeguard private keys; configure policies correctly

Developers

Secure application development; proper API integration

Infrastructure Operators

Maintain reliable and honest node operations

Protocol Governance

Maintain protocol integrity; coordinate upgrades

No single participant is solely responsible for ecosystem security.

Security Philosophy#

The Gao Internet security model is built on four principles:

Explicit authority verification — No action proceeds without cryptographic verification of the acting identity.

Deterministic policy enforcement — Policy evaluation produces consistent outcomes independent of who executes it.

Decentralized infrastructure resilience — No single node or operator failure can compromise the overall system.

Transparent auditability — Every significant action produces an immutable, inspectable audit record.

Security is achieved through a combination of architectural constraints, cryptographic mechanisms, and operational practices — not through trust in any single party.

Future Security Work#

Security models evolve as systems grow and new threat vectors emerge.

Future work may include:

  • Expanded threat analysis for new layer capabilities

  • Improved anomaly detection mechanisms

  • Enhanced policy verification tooling

  • Formal verification of core execution guarantees

  • Expanded infrastructure monitoring systems

Security improvements are introduced through protocol updates subject to governance processes and public documentation.

Gao Internet — Threat Model | GI-TM/1.0 | 2026-03-08 | Public – Security Reference