Zenodo DOI: 10.5281/zenodo.21379780 — Published 2026-07-15
Proof Protocol™ Living Threat Model
Document ID: PP-THREAT-001
Version: 1.0
Status: Living Document
License: Greater Good Commercial License 1.0 (GGL-C-1.0); text CC BY 4.0 under Part S. See LICENSE.md.
Maintained by: Proof Economy™ Standards Alliance (PESA)
Repository: https://github.com/proofprotocol
Published: 2026-07-14
Last Updated: 2026-07-14
Anchor: This document was first published on 2026-07-14 and anchored to the NIST Randomness Beacon at publication time. See
anchor-pulse.jsonin this repository for the tamper-resistant timestamp. All subsequent revisions are recorded in the git commit history of this repository, which constitutes the provenance chain for this living document.
What This Document Is
This is the Proof Protocol™'s living catalog of threat models the platform covers, tested against, and certifies. It is not a static whitepaper. It updates as the threat landscape changes and as new threat categories are formally covered by the specification suite.
Every threat model listed here is a category against which a ProofStamp™-certified benchmark run can be conducted. Entries are added when:
- A reference implementation run produces a certified ProofStamp™ record against the category
- A new threat category emerges that the platform architecture addresses
Version history is the git log of this file. The anchor-pulse.json in this repository establishes the earliest timestamp for version 1.0.
The Core Distinction
| Timing | Definition | Examples |
|---|---|---|
PRE-DATED |
The commitment exists before execution begins. NIST Beacon pulse captured before a single test case runs. The proof precedes the claim. Cannot be fabricated retroactively. | Pipelock PR-2026-00028 - pulse 1852788 captured before execution |
CONTINUOUS |
The benchmark is designed to test this category on an ongoing cadence as the threat landscape moves. Not a snapshot. Not a point-in-time audit. | All threat model categories in this document |
POST-DATED |
Documented threats that already existed at time of publication. Describes the known. Does not test the unknown. Does not move with the landscape. | OWASP Top 10 · MITRE ATLAS · NIST AI RMF · ISO 42001 · every framework in Section VI |
Proof Benchmark runs are pre-dated by design. Every other framework in the landscape is post-dated by nature.
Platform Architecture
| Component | Function |
|---|---|
| Arena7™ | Adversarial execution engine |
| CHOMP™ | Threat intelligence ingestion |
| SHRED™ | Threat intelligence processing - campaign stream identification |
| ProofWitness™ | Independent witness outside agent trust boundary |
| ProofBundler™ | Self-contained proof artifact assembly |
| ProofChain™ | NIST Beacon anchoring |
| ProofRegister™ | Public proof registry |
| Proof Protocol™ | Five-tier corroboration: Activated → Committed → Witnessed → Analyzed → Sealed |
| ProofStamp™ | Certification mark issued on conformant proof |
| PP-A2P™ | Agent-to-agent proof exchange protocol |
I. Traditional Enterprise Threat Models
| # | Threat Model | Notes |
|---|---|---|
| 1.1 | Advanced Persistent Threats (APT) | Multi-stage TTP execution across kill chain |
| 1.2 | Ransomware | Encryption, lateral movement, backup destruction |
| 1.3 | Supply Chain Compromise | Software injection, dependency poisoning, build pipeline |
| 1.4 | Zero-Day Exploitation | Pre-CVE techniques; intelligence pipeline ingests pre-disclosure channels |
| 1.5 | Credential Theft and Identity Abuse | PTH, PTT, Kerberoasting, Golden/Silver Ticket, LDAP abuse |
| 1.6 | Lateral Movement | Network traversal, pivot chains, trust relationship abuse |
| 1.7 | Living Off the Land (LOTL) | LOLBins, LOLDrivers, LOLScripts; no custom malware |
| 1.8 | Fileless Malware | Memory-resident; ProofWitness™ witnesses outside process boundary |
| 1.9 | Insider Threat | Authorized-credential misuse; hardest detection problem |
| 1.10 | Social Engineering and Phishing | Spear phishing, vishing, smishing, BEC |
| 1.11 | Command and Control (C2) | Beacon, DNS tunneling, HTTPS C2, domain fronting, fast-flux |
| 1.12 | Data Exfiltration | Staged, chunked, steganographic, cloud storage abuse |
| 1.13 | DDoS and Resource Exhaustion | Application-layer, connection exhaustion, amplification |
| 1.14 | Man-in-the-Middle and Protocol Abuse | TLS interception, ARP poisoning, BGP hijacking, cert abuse |
| 1.15 | Watering Hole and Drive-By | Malicious site injection, browser exploitation, plugin abuse |
| 1.16 | Physical and Hardware Attacks | BIOS/UEFI implant, hardware supply chain, physical access |
II. Cloud and Infrastructure Threat Models
| # | Threat Model | Notes |
|---|---|---|
| 2.1 | Cloud Misconfiguration Exploitation | S3 exposure, IAM privilege escalation, metadata service abuse |
| 2.2 | Container Escape | Docker breakout, K8s node compromise, runtime exploitation |
| 2.3 | Kubernetes Cluster Compromise | RBAC abuse, etcd exposure, API server exploitation |
| 2.4 | Serverless and Function Abuse | Lambda privilege escalation, event injection, cross-function lateral movement |
| 2.5 | CI/CD Pipeline Compromise | Build injection, artifact poisoning, secrets extraction |
| 2.6 | API Abuse and Business Logic | BOLA, BFLA, mass assignment, GraphQL introspection |
III. AI and Agentic Threat Models
| # | Threat Model | Notes |
|---|---|---|
| 3.1 | AI Agent Impersonation | PP-A2P™ requires proof exchange; impersonator cannot obtain ProofStamp™ |
| 3.2 | Prompt Injection - Direct and Indirect | Arena7™ executes injection chains; ProofWitness™ witnesses behavioral response |
| 3.3 | Multi-Agent Collusion | ProofWitness™ operates outside every agent trust boundary simultaneously |
| 3.4 | Agentic Supply Chain Compromise | Malicious tool introduced into agent workflow |
| 3.5 | Model Poisoning and Training Data Attacks | Adversarial probing of poisoned model behavior |
| 3.6 | AI-Generated Malware and Synthetic TTPs | Novel, polymorphic, pre-classification techniques |
| 3.7 | Adversarial AI vs Defensive AI | Arena7™ as adversarial AI; ProofWitness™ witnesses defensive AI |
| 3.8 | Agent Authorization Escalation | Chained tool calls, each authorized, collectively unauthorized |
| 3.9 | Agentic Worms and Self-Propagating Agents | Autonomous replication across systems, networks, or agent meshes |
| 3.10 | Synthetic Identity and Deepfake Social Engineering | AI-generated voice, video, text for impersonation |
| 3.11 | AI Hallucination Exploitation | Crafted inputs trigger false outputs used to justify unauthorized actions |
| 3.12 | Agent Memory and Context Poisoning | Malicious content injected into long-term memory or conversation context |
IV. Future and Day-Zero Threat Models
The platform architecture addresses threat categories that do not yet exist in any published taxonomy, CVE database, or threat intelligence feed. The proprietary intelligence pipeline ingests raw data before classification. The processing layer identifies actionable campaign streams before they are named. Arena7™ executes them. Proof Protocol™ attests the results with the same tamper-resistant record as any named TTP.
This is not a roadmap claim. The reference implementation - Pipelock v3.0.0, PR-2026-00028, NIST Beacon pulse 1852788 - demonstrates the architecture against current intelligence. The same pipeline scales to pre-classification data.
| # | Threat Model | Notes |
|---|---|---|
| 4.1 | Pre-CVE Zero-Day Exploitation | Intelligence pipeline ingests pre-disclosure channels |
| 4.2 | Novel Campaign Stream Detection | Processing layer identifies coherent streams from raw intake before naming |
| 4.3 | AI-Synthesized Zero-Day Techniques | No historical analog; not derivable from existing TTPs |
| 4.4 | Quantum-Enabled Cryptographic Attacks | Post-quantum techniques; NIST Beacon is NIST post-quantum aligned |
| 4.5 | Emergent Multi-Agent Threat Behaviors | Behaviors not programmed into any individual agent; first named here 2026-07-14 |
| 4.6 | Infrastructure AI Takeover | AI-assisted threat actor gains autonomous control of infrastructure |
| 4.7 | Agentic Ransomware | AI agent that adapts approach in real time based on defensive response |
| 4.8 | Regulatory Evidentiary Mandate | EU AI Act, DORA, NIS2, CMMC, FedRAMP High - every ProofStamp™ record satisfies evidentiary requirements |
V. Vertical Threat Models
| # | Vertical | Coverage |
|---|---|---|
| 5.1 | Financial Services | SWIFT abuse, payment rail manipulation, algorithmic trading attack, AML evasion via AI |
| 5.2 | Healthcare | EHR exploitation, medical device attack, HIPAA-relevant exfiltration, clinical ransomware |
| 5.3 | Critical Infrastructure (OT/ICS/SCADA) | PLC manipulation, historian exploitation, HMI attack, safety system bypass |
| 5.4 | Defense and Government | Nation-state TTP simulation, CMMC attestation; DoD CDAO Tradewinds TRL 7 |
| 5.5 | Telecommunications | SS7 exploitation, diameter protocol abuse, BGP hijacking, 5G core attacks |
VI. The Framework Landscape
Every published AI security framework as of July 2026, and what it cannot do.
| Framework | Owner | Type | What It Does | What It Cannot Do | |---------------|------|--------------|-------------------| | MAESTRO | CSA / Ken Huang (Feb 2025) | Governance | 7-layer threat identification for agentic AI | Produce evidence that any threat was tested or contained | | AICM | CSA | Governance | 243 controls across 18 domains | Attest any control was exercised under adversarial conditions | | ATF | CSA | Governance | Operationalizes AICM for agents; Zero Trust framing | Prove an agent operated within defined boundaries | | STAR for AI | CSAI Foundation | Governance | Catastrophic risk annex to CSA STAR | Produce contemporaneous execution evidence | | OWASP LLM Top 10 | OWASP (Aug 2023, updated 2025) | Taxonomy | Ranked LLM vulnerability list | Test for any or prove a system resists them | | OWASP Agentic Threats v1.0a | OWASP (Feb 2025) | Taxonomy | 15 agentic threat categories | Execute those threats or produce proof of containment | | OWASP Multi-Agentic Threat Modeling Guide | OWASP (Apr 2025) | Methodology | Structured threat modeling for multi-agent systems | Run the threat model or attest its results | | OWASP Top 10 for Agentic Applications 2026 | OWASP (Dec 2025) | Taxonomy | Top 10 agentic application risks | Certify a system's posture against any of the 10 | | MITRE ATLAS | MITRE | Taxonomy | Adversarial ML technique catalog | Execute techniques or produce certified containment records | | NIST AI RMF 1.0 | NIST | Governance | Govern, map, measure, manage AI risk | Produce adversarial execution evidence | | NIST AI 600-1 | NIST | Governance | Risk management for generative AI | Certify generative AI behavior under adversarial pressure | | NIST AI 100-2 | NIST | Taxonomy | Adversarial ML attacks and mitigations terminology | Test for any named attack or prove mitigation | | NIST CAISI Agent Standards Initiative | NIST (Feb 2026) | Governance | US government AI agent standards program | Produce anything certifiable; launched five months ago | | COSAiS | NIST | Governance | SP 800-53 control overlays for five AI use cases | Generate adversarial execution proof | | Google SAIF / SAIF 2.0 | Google | Vendor | Embed security into AI model development | Certify third-party systems | | Cisco DefenseClaw | Cisco (Mar 2026) | Vendor | Skills scanner, MCP scanner, AI BOM | Produce certified proof of adversarial containment; scan ≠ test | | Cisco AI Defense | Cisco | Vendor | Runtime guardrails and red teaming | Issue independent certification | | Palo Alto AIRS 3 | Palo Alto Networks | Vendor | Agent lifecycle security | Certify independently | | CrowdStrike AI Runtime Protection | CrowdStrike | Vendor | Runtime AI agent protection and shadow AI discovery | Produce tamper-resistant proof of containment | | Microsoft Entra Agent ID | Microsoft | Vendor | Agent identity within Microsoft enterprise perimeter | Attest agent behavior outside the Microsoft perimeter | | Anthropic Trustworthy Agents / Zero Trust for AI | Anthropic (Apr–May 2026) | Vendor | Model-layer safety and zero trust principles | Certify third-party systems | | AIUC-1 | AI Underwriting Consortium / Lovable (May 2026) | Governance | Six control families for coding agents | Independent adversarial execution proof; Lovable co-created and self-certified | | ASF | Jeff Sutherland | Governance | Agent Security Framework | Produce evidence of incidents it tracks | | MATRA | Academic | Taxonomy | Model the attack surface of agentic AI systems | Execute against that surface or certify results | | CoSAI | Linux Foundation | Governance | Coalition for Secure AI - working groups | Generate execution evidence | | C2PA | Content Provenance | Governance | Origin and edit history of media content | Cover runtime AI agent behavior | | EU AI Act | European Commission (Aug 2026) | Regulation | Risk-based requirements for AI systems in the EU | Specify which technical standard demonstrates compliance | | ISO/IEC 42001 | ISO | Governance | Certifiable AI management system | Produce adversarial execution proof; process audit, not a test | | DORA | EU | Regulation | Digital operational resilience for financial services | Define what constitutes adversarial test evidence | | NIS2 | EU | Regulation | Network and information security | Specify technical standard for AI-specific testing |
The Pattern
Every entry above is one of four things:
- Taxonomy - names threats. Does not test for them. Does not prove a system resists them.
- Governance framework - defines what controls should exist. Does not execute adversarial tests. Does not produce evidence.
- Vendor product - secures vendor customers. Not a disinterested third party. Cannot issue independent certification.
- Regulation - mandates outcomes. Does not specify the technical standard that demonstrates compliance. Creates demand for the proof. Does not supply it.
None of them is an execution framework operated by a structurally independent certifying authority that produces tamper-resistant proof at the protocol level.
Where Proof Protocol™ Sits
| Capability | Proof Protocol™ / HACKERverse | The Entire Landscape Above |
|---|---|---|
| Adversarial execution | Arena7™ runs the attack | None execute - they document |
| Pre-execution tamper-resistance | NIST Beacon commitment before execution begins | Not a feature of any framework |
| Day-zero / pre-CVE testing | Proprietary pipeline identifies emerging streams before classification | All are reactive to known threats |
| Independent witness | ProofWitness™ operates outside agent trust boundary | No framework provides structural independence |
| Numeric efficacy metric | PES - Containment and Detection over Blocked + Observed + Missed (PP-SPEC-006) | No framework defines a numeric efficacy metric |
| Tamper-resistant proof artifact | ProofBundle™ - self-contained, offline-verifiable | No framework produces execution evidence |
| Independent certification | ProofStamp™ - issued by disinterested third party | No equivalent |
| Agentic behavior attestation | ProofWitness™ witnesses agent behavior outside trust boundary | Existing frameworks describe controls; none attest behavior |
| Regulatory evidence | Every ProofStamp™ record satisfies EU AI Act, DORA, NIS2, CMMC evidentiary requirements | Regulations create the mandate; nothing else fills it |
| Structural independence | HACKERverse does not sell the products it certifies | Every vendor product certifies its own customers |
Reference Implementation
The first ProofStamp™-certified benchmark run:
| Field | Value |
|---|---|
| Product | Pipelock v3.0.0 |
| Proof Record ID | PR-2026-00028 |
| NIST Beacon Block | 29 |
| NIST Beacon Pulse Index | 1852788 |
| Applicable cases | 164 |
| Containment (PES) | 99.2% |
| Detection rate | 100% |
| False positive rate | 4.5% |
| Administered by | HACKERverse® Independent Test Lab |
| Certification date | 2026-07 |
This run predates any other published standard defining adversarial execution proof requirements for AI security tools. It is the reference implementation for threat models 1.1 through 4.8.
Revision History
| Version | Date | Changes | Anchor |
|---|---|---|---|
| 1.0 | 2026-07-14 | Initial publication. 40 threat models across 5 sections. Framework landscape table (30 entries). | See anchor-pulse.json |
This is a living document. Changes are tracked in the git commit history of this repository. Each significant revision will be accompanied by a new NIST Beacon pulse anchor committed alongside the updated file.
CC BY 4.0 - Attribution to Craig Ellrod / Nebulonium, Inc. required.
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