探花视频, in conjunction with its vendor partners, sponsors hundreds of events each year, ranging from webcasts and tradeshows to executive roundtables and technology forums.
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Procuring in the Dark: Unmasking Hidden Risks in AI-Generated and Third-Party Software
Hosted By: Unknown Cyber & 探花视频
Unknown Cyber’s Software Scan offered a revolutionary, deterministic approach to verifying third-party software upon delivery, directly answering Gartner’s call to perform Binary Composition Analysis (BCA) on high-risk software. Powered by DARPA-developed genomic analysis, it mathematically computed the ultimate effects of every function on registers and memory. This meant compliance professionals, risk managers, and leaders were able to achieve unprecedented, auditable accuracy regarding exactly what was inside their vendors’ binaries, without ever needing the proprietary source code. By moving from probabilistic guesswork to deterministic truth, organizations were able to embed continuous monitoring into procurement, establish a verifiable Zero Trust posture, and confidently meet CMMC 2.0 mandates.
Attendees joined Unknown Cyber to discover how to operationalize Gartner’s recommendations for supply chain security, replacing blind trust and incomplete SBOMs with deterministic mathematical verification at the time of procurement.
What Attendees Learned:
- The financial and board-level impact of software supply chain breaches, which had seen a 100% year-over-year growth.
- Why Gartner explicitly recommended embedding Binary Composition Analysis (BCA) into procurement and renewal contracts to technically validate software and supplier SBOMs.
- How the rise of AI-generated code was silently injecting vulnerabilities into commercial software (with AI failing to write secure code 45% of the time).
- The critical flaw in probabilistic scanning methods that relied on surface-level file structures, and why they failed as a “black box” against modern threats.
- How organizations could achieve deterministic, auditable accuracy by analyzing the mathematical effects of software functions on registers and memory—without needing vendor source code.
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