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.
Cite as
Ellrod, C. (2026). Proof Protocol Living Threat Model. Proof Economy Standards Alliance (PESA). https://doi.org/10.5281/zenodo.21379780
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. | Frameworks discussed 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 | Timing |
|---|---|---|---|
| 1.1 | Advanced Persistent Threats (APT) | Multi-stage TTP execution across kill chain | CONTINUOUS |
| 1.2 | Ransomware | Encryption, lateral movement, backup destruction | CONTINUOUS |
| 1.3 | Supply Chain Compromise | Software injection, dependency poisoning, build pipeline | CONTINUOUS |
| 1.4 | Zero-Day Exploitation | Pre-CVE techniques; intelligence pipeline ingests pre-disclosure channels | CONTINUOUS |
| 1.5 | Credential Theft and Identity Abuse | PTH, PTT, Kerberoasting, Golden/Silver Ticket, LDAP abuse | CONTINUOUS |
| 1.6 | Lateral Movement | Network traversal, pivot chains, trust relationship abuse | CONTINUOUS |
| 1.7 | Living Off the Land (LOTL) | LOLBins, LOLDrivers, LOLScripts; no custom malware | CONTINUOUS |
| 1.8 | Fileless Malware | Memory-resident; ProofWitness™ witnesses outside process boundary | CONTINUOUS |
| 1.9 | Insider Threat | Authorized-credential misuse; hardest detection problem | CONTINUOUS |
| 1.10 | Social Engineering and Phishing | Spear phishing, vishing, smishing, BEC | CONTINUOUS |
| 1.11 | Command and Control (C2) | Beacon, DNS tunneling, HTTPS C2, domain fronting, fast-flux | CONTINUOUS |
| 1.12 | Data Exfiltration | Staged, chunked, steganographic, cloud storage abuse | CONTINUOUS |
| 1.13 | DDoS and Resource Exhaustion | Application-layer, connection exhaustion, amplification | CONTINUOUS |
| 1.14 | Man-in-the-Middle and Protocol Abuse | TLS interception, ARP poisoning, BGP hijacking, cert abuse | CONTINUOUS |
| 1.15 | Watering Hole and Drive-By | Malicious site injection, browser exploitation, plugin abuse | CONTINUOUS |
| 1.16 | Physical and Hardware Attacks | BIOS/UEFI implant, hardware supply chain, physical access | CONTINUOUS |
II. Cloud and Infrastructure Threat Models
| # | Threat Model | Notes | Timing |
|---|---|---|---|
| 2.1 | Cloud Misconfiguration Exploitation | S3 exposure, IAM privilege escalation, metadata service abuse | CONTINUOUS |
| 2.2 | Container Escape | Docker breakout, K8s node compromise, runtime exploitation | CONTINUOUS |
| 2.3 | Kubernetes Cluster Compromise | RBAC abuse, etcd exposure, API server exploitation | CONTINUOUS |
| 2.4 | Serverless and Function Abuse | Lambda privilege escalation, event injection, cross-function lateral movement | CONTINUOUS |
| 2.5 | CI/CD Pipeline Compromise | Build injection, artifact poisoning, secrets extraction | CONTINUOUS |
| 2.6 | API Abuse and Business Logic | BOLA, BFLA, mass assignment, GraphQL introspection | CONTINUOUS |
III. AI and Agentic Threat Models
| # | Threat Model | Notes | Timing |
|---|---|---|---|
| 3.1 | AI Agent Impersonation | PP-A2P™ requires proof exchange; impersonator cannot obtain ProofStamp™ | CONTINUOUS |
| 3.2 | Prompt Injection - Direct and Indirect | Arena7™ executes injection chains; ProofWitness™ witnesses behavioral response | CONTINUOUS |
| 3.3 | Multi-Agent Collusion | ProofWitness™ operates outside every agent trust boundary simultaneously | CONTINUOUS |
| 3.4 | Agentic Supply Chain Compromise | Malicious tool introduced into agent workflow | CONTINUOUS |
| 3.5 | Model Poisoning and Training Data Attacks | Adversarial probing of poisoned model behavior | CONTINUOUS |
| 3.6 | AI-Generated Malware and Synthetic TTPs | Novel, polymorphic, pre-classification techniques | CONTINUOUS |
| 3.7 | Adversarial AI vs Defensive AI | Arena7™ as adversarial AI; ProofWitness™ witnesses defensive AI | CONTINUOUS |
| 3.8 | Agent Authorization Escalation | Chained tool calls, each authorized, collectively unauthorized | CONTINUOUS |
| 3.9 | Agentic Worms and Self-Propagating Agents | Autonomous replication across systems, networks, or agent meshes | CONTINUOUS |
| 3.10 | Synthetic Identity and Deepfake Social Engineering | AI-generated voice, video, text for impersonation | CONTINUOUS |
| 3.11 | AI Hallucination Exploitation | Crafted inputs trigger false outputs used to justify unauthorized actions | CONTINUOUS |
| 3.12 | Agent Memory and Context Poisoning | Malicious content injected into long-term memory or conversation context | CONTINUOUS |
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 | Timing |
|---|---|---|---|
| 4.1 | Pre-CVE Zero-Day Exploitation | Intelligence pipeline ingests pre-disclosure channels | CONTINUOUS |
| 4.2 | Novel Campaign Stream Detection | Processing layer identifies coherent streams from raw intake before naming | CONTINUOUS |
| 4.3 | AI-Synthesized Zero-Day Techniques | No historical analog; not derivable from existing TTPs | CONTINUOUS |
| 4.4 | Quantum-Enabled Cryptographic Attacks | Post-quantum techniques; NIST Beacon is NIST post-quantum aligned | CONTINUOUS |
| 4.5 | Emergent Multi-Agent Threat Behaviors | Behaviors not programmed into any individual agent; first named here 2026-07-14 | CONTINUOUS |
| 4.6 | Infrastructure AI Takeover | AI-assisted threat actor gains autonomous control of infrastructure | CONTINUOUS |
| 4.7 | Agentic Ransomware | AI agent that adapts approach in real time based on defensive response | CONTINUOUS |
| 4.8 | Regulatory Evidentiary Mandate | EU AI Act, DORA, NIS2, CMMC, FedRAMP High - every ProofStamp™ record satisfies evidentiary requirements | CONTINUOUS |
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
As of July 2026, the published AI security and governance landscape falls into four categories. None of them, individually or collectively, produce adversarial execution evidence at the protocol level.
Taxonomies
Threat and vulnerability taxonomies name and classify risks — ranked vulnerability lists, technique catalogs, and threat modeling guides for agentic and LLM systems. They give the industry shared vocabulary for what can go wrong. They do not execute tests against the risks they name, and they do not produce evidence that a given system resists them.
Governance Frameworks
Governance frameworks define what controls, layers, or risk-management processes should exist — control catalogs, layered threat-identification models, risk management frameworks, and management-system standards. They describe the shape of a defensible program. They do not run adversarial tests and do not themselves produce execution evidence; several require or recommend third-party assessment, but the assessment is a process review, not an adversarial proof artifact.
Vendor Products
Individual security vendors ship runtime guardrails, agent identity systems, red-teaming tools, and AI bill-of-materials scanners as part of their own product lines. These are real and often valuable capabilities. Structurally, though, a vendor's own tooling is not a disinterested third party with respect to its own customers, and none of these products issue independent, cross-vendor certification.
Regulations
Regulatory frameworks (the EU AI Act, DORA, NIS2, and comparable regimes) mandate outcomes — risk-based requirements, operational resilience, network security — without specifying the technical standard that demonstrates compliance. They create the demand for verifiable evidence. They do not supply the evidentiary mechanism themselves.
The Pattern
Every framework in the current landscape is one of these 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 Landscape Above |
|---|---|---|
| Adversarial execution | Arena7™ runs the attack | Documented, not executed |
| Pre-execution tamper-resistance | NIST Beacon commitment before execution begins | Not a feature of taxonomies, governance frameworks, or regulations |
| Day-zero / pre-CVE testing | Proprietary pipeline identifies emerging streams before classification | Reactive to known, classified threats |
| Independent witness | ProofWitness™ operates outside agent trust boundary | Structural independence not provided by vendor tooling |
| Numeric efficacy metric | PES - Containment and Detection over Blocked + Observed + Missed (PP-SPEC-006) | No numeric efficacy metric defined |
| Tamper-resistant proof artifact | ProofBundle™ – self-contained, offline-verifiable | Execution evidence not produced |
| Independent certification | ProofStamp™ – issued by a disinterested third party | Vendor products certify their own customers, not independently |
| Agentic behavior attestation | ProofWitness™ witnesses agent behavior outside trust boundary | Controls are described; behavior is not attested |
| 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 | Vendor products certify their 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 | Nebulonium, Inc. (d/b/a 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 section (four categories, generalized). | 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. Proof Economy™ Standards Alliance (PESA) - proofprotocol.io "Proof is the new Currency"