This post is a guest contribution by George Siosi Samuels, managing director at Faiā. See how Faiā is committed to staying at the forefront of technological advancements here.
TL;DR: Generative AI is shifting the enterprise cybersecurity perimeter from networks and endpoints to language models, prompts, and agentic workflows. This new terrain introduces vulnerabilities that traditional tools can’t see. Blockchain—specifically, BSV’s Teranode architecture—offers a pathway toward immutable, scalable, and transparent defenses. Together, they signal the next evolution of digital trust.
When language becomes the new attack surface
In a recent interview I did with Eito Miyamura, founder of a new startup called Edison Watch, he revealed how easily artificial intelligence (AI) agents can be hijacked with something as ordinary as an email or calendar invite.
“All it really requires is three things… inject a malicious prompt… ability for the agent to look through some private data… and then finally… ability to write the data,” said Miyamura.
In his demonstration, a malicious calendar invite contained an embedded prompt injection that allowed a ChatGPT-connected agent to access and exfiltrate private emails. No malware. No exploit kits. Just words interpreted as executable code.
This single example reframes how we think about cybersecurity. In the age of generative AI:
- Language = code
- Prompts = commands
- Agents = autonomous executors
Each untrusted message or document could be a potential command that hijacks an AI agent’s logic, privileges, or toolset.
The multiplication of risk in the tool-enabled era
Miyamura highlighted a pattern spreading across enterprises: enabling every possible connector in Multi-Connector Platforms (MCPs) like it’s harmless. But each connected API—from Gmail to
Notion—is an open circuit waiting for misuse.
“Not turning all of the tools on… only turning on what you need… making sure that no data is being exfiltrated.”
The combination of permissive tool access and unfiltered prompts creates new compound risks:
- Prompt injections that exploit untrusted content (emails, PDFs, websites)
- Agent privilege escalation via broad API access
- Typosquatting in AI libraries, injecting malicious code through lookalike packages
- SEO-optimized jailbreaks, manipulating agents into false beliefs or actions
These vectors thrive in environments optimized for speed over scrutiny. Enterprises are entering what could be called “Phishing 3.0,” where the bait isn’t a link, but a well-crafted sentence.
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The current security gap
Today’s Security and Operation Centers (SOCs) and Endpoint and Detection Response (EDR) tools aren’t built to monitor or intercept malicious language patterns. The traditional firewall cannot see inside model prompts or agent reasoning chains. Miyamura warns that the MCP ecosystem is immature and not ready for broad production use.
His company, Edison Watch, is addressing this by building AI firewalls and data valves—open-source guardrails designed to prevent exfiltration through deterministic checks. In time, these could evolve into a new class of agent security gateways.
“We are essentially building data firewalls and data valves to make sure data stays where it should… and prevent exfiltration attacks.”
The next logical step? Layered protection. Miyamura calls it the “bodyguard agent” model—agents that monitor and constrain other agents. But even bodyguards need a trustworthy ledger.
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Blockchain as the next line of defense
Blockchain has evolved beyond just finance now—it’s becoming essential infrastructure for verifiable computing. Immutable ledgers allow us to trace not just transactions, but prompts, tool calls, and agent behaviors. In this context, BSV’s Teranode architecture stands out.
Why Teranode matters
Teranode represents a complete re-engineering of node software on the BSV network, designed for enterprise-grade scalability:
- Millions of transactions per second have been demonstrated under test conditions.
- Microservices architecture allows dynamic scaling for global workloads.
- Low-latency validation enables real-time logging and policy enforcement.
Such capacity transforms what blockchain can do for cybersecurity:
- Immutable Audit Trails: Every prompt, API call, or model action can be logged on-chain, creating a tamper-resistant record for incident forensics.
- Agent Attestation: Each AI agent can register its signature, permissions, and activity logs on the ledger—verifiable across enterprise systems.
- Smart-Contract Guardrails: On-chain rules can define what an agent is allowed to execute or send, automatically halting rogue behavior.
- Cross-System Integrity: Blockchain becomes a single source of truth across distributed AI systems, preventing inconsistent or falsified states.
Together, this forms the foundation of a ledger-based trust fabric for the AI era—one that can scale to billions of autonomous interactions without sacrificing integrity.
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From detection to conscious alignment
As generative AI systems become integral to enterprise workflows, cybersecurity can no longer be reactive. We need systems that align, not just defend. That means:
- Designing agent-aware governance, where every AI action is observable and accountable.
- Embedding ledger-backed integrity at the protocol layer, not as an afterthought.
- Encouraging procedural adoption—turning on only the tools you need, validating every write, and reviewing every send.
In this new terrain, blockchain isn’t competing with AI anymore. It’s completing it. Immutable, verifiable records turn agentic uncertainty into traceable accountability.
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Looking ahead
The next decade will not be defined by whether AI can think, but by whether we can trust what it does. Generative models will continue to evolve—from assistants to autonomous systems. Without verifiable audit layers, every enterprise will be flying blind.
The combination of AI firewalls (like Edison Watch’s) and blockchain infrastructures (like BSV’s Teranode) outlines a practical blueprint for resilient digital ecosystems.
Your enterprise perimeter now ends where your language model begins.
The only way forward is to rebuild trust at the architectural level—and blockchain may already be showing the way.
In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.
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Watch: Demonstrating the potential of blockchain’s fusion with AI
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Source: https://coingeek.com/how-generative-ai-models-fuel-new-attack-vectors/
