Addressing the proliferation of offensive AI tools, Assail Founder and CEO will deliver a presentation discussing a new framework for evaluating harness orchestration and governance over raw LLM capabilities.
BOSTON, July 28, 2026 /PRNewswire/ — Assail, the pioneer in autonomous red teaming powered by recursive self-improvement AI, will host a dedicated Lunch & Learn presentation and accompanying industry panel at Black Hat 2026, one of the industry’s biggest stages. Assail founder, CEO and Chief AI Officer Alissa Knight will deliver a session titled, “The Harness Wars: How AI Harnesses Will Decide the Future of Offensive Cyber,” from 12:05 p.m.–1:35 p.m. on Wednesday, Aug. 5, at the Lagoon Conference Center located in the Mandalay Bay South Convention Center in Las Vegas. The presentation will introduce a critical corrective framework for evaluating offensive AI tools flooding the market, challenging the industry’s tendency to judge autonomous systems solely by their underlying LLMs.
“We have seen a rapid rise of AI in offensive security over the past couple years, but the industry is still evaluating these tools through the wrong lens,” Knight said. “The model is just the weapon; the harness is the actual operator. What separates a real autonomous attacker from a marketing demo is orchestration, memory, and split-second judgment of what to do next. That is where offense lives. I look forward to sharing our raw, hands-on experience building this architecture, detailing what works, what fails and why the harness, not the model, will ultimately decide the future of AI cyber warfare.”
Drawing on 26 years of hacking experience and her background as principal architect of autonomous offensive systems, Knight will lead a session examining why commoditized model benchmarks reveal only part of the AI risk picture. She will demonstrate how harness architecture, orchestration, governance and model-adapted weights ultimately shape system behavior and determine risk. Following the presentation, Knight will host a panel discussion featuring industry leaders Eric Wood, security and compliance manager at Peregrine; David Tyburski, CISO of Wynn; and Martin Rieger, Chief Solutions Officer at Qanapi, to elevate the event into a collaborative industry dialogue addressing the systemic challenges of securing and deploying offensive AI tooling and the future of their frameworks.
“Evaluating autonomous security platforms simply by their underlying LLMs is a dead end for buyers and enterprise leaders in this rapidly evolving space,” states Wood. “As foundation models converge in capability, the real differentiators for enterprise security teams and the true driver of operational risk is how these systems are built and managed. Organizations will quickly realize that real security value lies in the harness architecture that actually guides, governs and deploys these systems in production.”
As a trailblazer in autonomous offensive AI, Assail’s own technology demonstrates the growing importance of sophisticated execution frameworks. The company recently introduced Ares™ v2, powered by its new Sidewinder™ harness and AI model. The complete redesign of Assail’s flagship autonomous offensive security platform, includes a new interface, a purpose-built model and a rebuilt agentic harness that enables the system to audit her own work, identify and correct errors, adapt its approach and improve execution over time. Ares v2 provides a real-world example of how harness architecture, orchestration and governance, rather than the underlying model alone, shape autonomous capabilities and risk.
For more information on Assail’s autonomous solutions or to receive an invitation to the Black Hat Lunch & Learn event, visit www.assailai.com.
About Assail AI
Assail is a cybersecurity company building autonomous offensive AI for the modern application stack. Founded by Alissa Knight and headquartered in Boston, Massachusetts, Assail’s flagship platform, Ares, deploys self-evolving AI agents that discover, chain, and exploit vulnerabilities across APIs, mobile apps, and web applications, teaching themselves novel attack techniques through adversarial co-evolution without reliance on human-curated training data. For more information, visit assailai.com
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SOURCE Assail, Inc.
