Source: Black Hills Information Security, Inc.
Author: BHIS
URL: https://www.blackhillsinfosec.com/introducing-fusion-ai/
Everyone’s Selling AI That Kills Pentesting. We Built One That Doesn’t.
ONE SENTENCE SUMMARY:
Fusion AI augments external penetration testing with transparent, methodology-driven agents and human verification, lowering costs while improving coverage against AI-enabled attackers.
MAIN POINTS:
- Market hype claims agentic red teams will replace pentesters; Fusion AI rejects that premise.
- Offering costs about one-third of traditional external pentests, keeping humans in final control.
- Originated from an internal challenge to build an AI-powered external testing capability.
- Initial prototypes used Claude Code before evolving into a custom agentic investigation platform.
- Core differentiator is embedding BHIS testing methodology, not merely automating scanner output.
- Agents prioritize chaining medium/low/informational findings into impactful exploit paths.
- Platform provides full transparency: commands, steps, validation evidence, and reproducibility details.
- Motivation included adversaries adopting AI, highlighted by Anthropic’s report on Chinese actor misuse.
- Pilot testing focused on reducing hallucinations and improving actionable output quality.
- Real-world coverage win: detected compromised site via injected gambling links and likely exploit chain.
TAKEAWAYS:
- Human-in-the-loop review remains essential for severity accuracy and false-positive control.
- Methodology and institutional knowledge matter more than “AI-powered” branding.
- Transparent audit trails help solve AI interpretability and enable reliable verification.
- Automation can uncover tedious indicators humans often miss under tight engagement timelines.
- Lower-cost external testing expands access for smaller organizations previously priced out.