The Good Tech Companies - Inside the AI-Driven Supply Chain: How Scribe Security Is Building Trust at Code Speed

Episode Date: September 30, 2025

This story was originally published on HackerNoon at: https://hackernoon.com/inside-the-ai-driven-supply-chain-how-scribe-security-is-building-trust-at-code-speed. Scribe Security’s ScribeHub combines signed provenance, SBOMs, and AI agents to secure AI-generated code and meet global supply chain regulations. Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #software-supply-chain-security, #ai-generated-code-risks, #scribe-security, #scribehub-platform, #sbom-and-provenance, #ai-remediation-agents, #secure-software-development, #good-company, and more. This story was written by: @jonstojanjournalist. Learn more about this writer by checking @jonstojanjournalist's about page, and for more stories, please visit hackernoon.com. With over 50% of code projected to be AI-generated by 2025, supply chain risks are rising. Scribe Security’s ScribeHub platform captures signed evidence across the SDLC, links it in a tamper-proof graph, and enforces policy guardrails. AI agents like Remus and Compy automate fixes and compliance, helping CISOs balance speed with trust while meeting regulatory demands.

This audio is presented by Hacker Noon, where anyone can learn anything about any technology. Inside the eye-driven supply chain, how Scribe Security is building trust at code speed by John Stoy and journalist. Photo courtesy of Scribe Security the adoption of AI assistance such as GitHub co-pilot has transformed software development. Analysts estimate that by 2025, more than 50% of new code will be machine generated, according to Gardner. While this has accelerated productivity, it has also created new security challenges. Automated suggestions often contain misconfigurations, exposed secrets, or unpatched

vulnerabilities. For companies managing thousands of repositories and dependencies, this flood of AI-produced code expands an already complex attack surface. A 2024 report from IBM found that the average cost of a data breach reached $4.45 million, with supply chain vulnerability, cited as one of the fastest growing sources of exposure. Governments in the United States, European Union, and Japan have introduced stricter requirements for verifiable software provenance, pressing companies to adopt security mechanisms that contract the origin and integrity of every artifact. Development speed has accelerated beyond the reach of manual inspection, said Ruby Arbel, CEO of Scribe Security. Organizations need systems that validate and record every step,

whether code is written by humans or generated by AI. Continuous evidence and policy guardrails. Scribe Security has built its Scribe Hub platform around the idea that security cannot be a one-time check. Instead of relying solely on periodic cans, Scribe Hub collects signed evidence during each phase of the software development lifecycle. This includes software bills of materials, SBOMs, scanner results, and provenance records, all transformed into machine-readable at stations. The evidence is stored in a tamper-proof knowledge graph linking artifacts, identities, and actions. This allows security teams to trace vulnerabilities back to specific commits, tools, or configurations. Policies written as code act as guardrails,

blocking unverified or tampered artifacts from progressing to deployment. Developers see the impact through contextual feedback, with the option to trigger automated fixes without leaving their workflows. This method has gained traction among regulated industries, where compliance, compliance frameworks such as SLSA, NIST SSDF, and the EU's Cyber Resilience Act require proof that software components meet defined security standards. By embedding checks early and maintaining cryptographic records, organizations reduce the risk of last-minute failures or audit deficiencies. Agentic Security. AI for remediation. The introduction of I-generated code prompted scribe security to add a new dimension, AI-driven remediation. Rather than bolting algorithms onto dashboards, the company designed a network of task-specific agents that interact with the signed knowledge graph. Each agent specializes in a function, triaging vulnerabilities, generating secure patches, analyzing Docker files, or drafting compliance reports.

One example is, Remus, an agentic workflow capable of producing pull requests to patch and secure dependencies or configuration files. Another, Compi, continuously compares signed evidence against a. standards such as PCIDSS ORFEDRAMP, producing audit-ready documentation as part of everyday development. These functions are designed to reduce the time between detection and resolution, cutting what once took weeks into hours. I-generated fixes only work if they are tied to verified evidence, Arbel explained. By combining signed provenance with automated remediation, we reduce both human workload and the likelihood of introducing new errors. Implications for CSOs and developers, Chief Information Security Officers face mounting pressure to reconcile speed with accountability.

In many organizations, security staff are outnumbered by developers at ratios as high as 1 to 100. Without automation, investigating alerts and preparing for audits can overwhelm teams. According to a 2025 survey B-SACA, 66% of companies reported difficulty filling cybersecurity roles, particularly in software supply chain security. For developers, traditional security processes are often experienced AS bottlenecks. By integrating evidence collection and agent-driven remediation directly into the tools they already use, friction is reduced. Pull requests arrive with explanations, policies are enforced consistently, and compliance reports are generated continuously. The result is a development cycle that moves quickly without bypassing security requirements.

Market forces and regulatory drivers. The cyber security market is projected to grow from $262 billion in 2025 to morethin $350 billion by 2030, with software supply chain security cited as one of the highest priority investment areas. In the U.S., Executive Order 14,28, 14,144, and NIST SSDF mandate federal contractors to produce SBOMs, while Europe's Cyber Resilience Act introduces similar requirements for technology vendors. government has also advanced legislation to enhance monitoring of supply chain risks, with implementation deadlines approaching by 2027. These regulatory pressures align with the increasing prevalence of AI in development. Companies can no longer rely on ad hoc fixes. They must demonstrate

continuous verification of their software factories. Solutions that combine cryptographic integrity checks, evidence trails, and AI remediation are quickly moving from optional to necessary. Trust in software now depends on being able to prove how it was built, Arbell said. That proof must be generated at the same speed as the code itself. Thank you for listening to this Hackernoon story, read by artificial intelligence. Visit hackernoon.com to read, write, learn and publish.