# Resource-Optimized and Energy-Aware Agentic AI Framework Anchored on Blockchain for Secure Software Supply Chains

arXiv: https://arxiv.org/abs/2609.31282 · HTML: https://mlsanity.com/paper/2609.31282/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 35 references that are in the map.
- First posted on arXiv 25 Sep 2026.

## Builds on (most cited first, 17 of 17)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Agents: An Open-source Framework for Autonomous Language Agents](https://mlsanity.com/paper/2309.07870/) (2023)
- [Backstabber's Knife Collection: A Review of Open Source Software Supply Chain Attacks](https://mlsanity.com/paper/2005.09535/) (2020)
- [Taxonomy of Attacks on Open-Source Software Supply Chains](https://mlsanity.com/paper/2204.04008/) (2022)
- [SAGA: A Security Architecture for Governing AI Agentic Systems](https://mlsanity.com/paper/2504.21034/) (2025)
- [Agentic LLMs in the Supply Chain: Towards Autonomous Multi-Agent Consensus-Seeking](https://mlsanity.com/paper/2411.10184/) (2024)
- [Agentic AI Framework for Individuals with Disabilities and Neurodivergence: A Multi-Agent System for Healthy Eating, Daily Routines, and Inclusive Well-Being](https://mlsanity.com/paper/2511.22737/) (2025)
- [Toward Trustworthy Agentic AI: A Multimodal Framework for Preventing Prompt Injection Attacks](https://mlsanity.com/paper/2512.23557/) (2025)
- [Deep Reinforcement Learning for Autonomous Cyber Defence: A Survey](https://mlsanity.com/paper/2310.07745/) (2023)
- [SoK: Analysis of Software Supply Chain Security by Establishing Secure Design Properties](https://mlsanity.com/paper/2406.10109/) (2024)
- [Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review](https://mlsanity.com/paper/2206.02733/) (2022)
- [Security Vulnerabilities in Software Supply Chain for Autonomous Vehicles](https://mlsanity.com/paper/2509.16899/) (2025)
- [Reinforcement Learning for Hardware Security: Opportunities, Developments, and Challenges](https://mlsanity.com/paper/2208.13885/) (2022)
- [What is Software Supply Chain Security?](https://mlsanity.com/paper/2209.04006/) (2022)
- [An Empirically Grounded Reference Architecture for Software Supply Chain Metadata Management](https://mlsanity.com/paper/2310.06300/) (2023)
- [Agentic AI for Autonomous Defense in Software Supply Chain Security: Beyond Provenance to Vulnerability Mitigation](https://mlsanity.com/paper/2512.23480/) (2025)
- [ARGO-SLSA: Software Supply Chain Security in Argo Workflows](https://mlsanity.com/paper/2503.20079/) (2025)

## Abstract (arXiv)

This paper proposes a blockchain-backed agentic security framework designed to safeguard the complete software development lifecycle (SDLC) while also securing the agentic AI components responsible for monitoring it. The framework coordinates a set of specialised security agents, covering source integrity, dependency and SBOM analysis, CI configura tion auditing, artifact verification, and runtime policy evaluation, each supported by a large language model (LLM) that interprets artefacts, reasons over tool outputs, and produces structured security reports. To ensure agent trustworthiness, every agent generates a cryptographically signed attestation that is recorded in a permissioned blockchain via smart contracts, including an agent registry, an immutable attestation log, and an enforceable release-policy module. Communication among agents and with blockchain nodes is secured using a consortium-operated certificate authority, ensuring authenticated and tamper-resistant interactions. A detailed use-case and sequence flow demonstrate how a source code security agent performs analysis, anchors its attestation on-chain, and triggers a verifiable allow/block deployment decision. The proposed framework of fers decentralised integrity transparent provenance, uninterrupted security assurance and a generalisable architecture to incorporate the agentic AI into the modern software supply chain security.