July 2026 Summaries

Bugcrowd has launched Savant Pathseeker, an early access agentic pentesting solution designed to enhance pentesting coverage across neglected applications and APIs with increased speed, scalability, and affordability. Traditional pentesting methods were limited, often failing to significantly reduce risk or uncover unknown vulnerabilities. The advent of automated pentesting, particularly through AI, offers broader and more frequent testing, although it can result in high false-negative rates, missing complex issues like business logic. Hybrid pentesting combines the extensive reach of AI with the nuanced judgment of human experts, ensuring more accurate results by addressing gaps that automated tools might overlook. This approach retains the benefits of automation while leveraging human insights to validate and prioritize findings, thus enhancing the overall effectiveness of security assessments without sacrificing coverage or speed.

Bugcrowd is hosting a series of events during Black Hat and DEF CON week, creating opportunities for networking and discussions on cybersecurity and AI. The Hive, an event co-hosted with HPE Networking at Swingers Las Vegas, promises engaging activities like mini golf, chess, and panels featuring security leaders and ethical hackers discussing AI's impact on hacking. Attendees can enjoy snacks, beverages, and nostalgic Bugcrowd swag, including stickers, posters, and copies of "The Hacker Culture Manual." Sponsors like Pi Security, Cytix, Vijil, and Manifold Security will showcase their innovative cybersecurity solutions, offering insights into vulnerability management and AI agent trustworthiness. The Hive aims to foster conversations and connections among attendees, continuing the dynamic exchanges initiated at Black Hat.

Bugcrowd has introduced Savant Pathseeker, an agentic pentesting solution designed to autonomously identify vulnerabilities in web applications and APIs at machine speed, providing evidence of exploitability. This tool enhances Bugcrowd's platform by supporting the entire preemptive security testing lifecycle, enabling continuous asset scanning and threat neutralization before exploitation by attackers. The increasing complexity of attack surfaces due to cloud, SaaS, and API expansion, alongside the rise of AI-generated code vulnerabilities, necessitates such automated solutions. Pathseeker integrates AI-driven testing with human validation to ensure comprehensive security coverage by delivering risk-ranked results and prioritizing critical vulnerabilities, while also facilitating compliance with evolving regulatory requirements. Unlike traditional methods, Pathseeker combines autonomous testing and human expertise within a single platform, leveraging both AI models and Bugcrowd's extensive experience in offensive security. This approach allows security teams to maintain a balance between automated breadth and human-led depth in testing, thus improving overall security posture without increasing costs.

In a recent AI lecture series based on a talk at Carnegie Mellon University, the complexities and potential vulnerabilities of modern AI systems were explored, emphasizing the importance for Chief Information Security Officers (CISOs) to understand these aspects for effective security governance. AI systems, often treated as black boxes, should instead be dissected into their core training stages—pretraining, Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human Feedback (RLHF)—each presenting unique security risks such as corpus and demonstration poisoning. The lecture highlighted how the context window at inference time poses significant security concerns since it includes unstructured text from various sources, which can be misinterpreted as instructions, thus lacking a structural trust boundary. Furthermore, the integration of tools and agents in LLM deployments expands the threat model, allowing models to perform actions that could result in adversarial outcomes. Governance requires careful consideration of training data provenance, model supply chain integrity, context window composition, tool permissions, and agent autonomy settings. These considerations are crucial for organizations seeking to mitigate risks before regulatory demands intensify, with future discussions in the series set to address securing the AI attack surface.

Dr. David Brumley, Chief AI Officer at Bugcrowd and a professor at Carnegie Mellon University, discusses the complexities of AI security, emphasizing the importance of understanding AI as a set of distinct mechanisms rather than a monolithic technology. He highlights how different AI mechanisms—such as machine learning, symbolic reasoning, search and planning, probabilistic AI, and hybrid systems—each have unique attack surfaces and security vulnerabilities. For example, machine learning models are prone to adversarial inputs, while symbolic reasoning systems are vulnerable through their knowledge bases. Brumley advises security leaders to ask critical questions about AI systems, such as the mechanisms involved and the system's architecture, to make informed governance and security decisions. He underscores the need for organizations to distinguish between AI as a goal and as a technique for effective policy development, noting that a significant portion of enterprises are already utilizing AI tools. The blog post serves as part of a lecture series aimed at educating security leaders on the anatomy and governance of AI systems.

In a recent panel hosted by Bugcrowd, experts discussed the challenges posed by AI-generated vulnerability reports, which have dramatically increased the volume of valid findings in enterprise security. This phenomenon, termed "AI slop," refers to the influx of low-quality, often hallucinated vulnerability submissions that accompany legitimate discoveries, complicating the task of distinguishing actionable threats. The conversation highlighted that while AI enhances capabilities like external reconnaissance and vulnerability discovery, it has yet to significantly impact internal attack techniques. The key to managing the overwhelming number of vulnerabilities is context; organizations must prioritize findings based on their potential to threaten critical assets, utilizing frameworks like MITRE ATT&CK and integrating human judgment from red team exercises. This approach emphasizes the importance of understanding the full attack path to an asset and focusing on threats most likely to be exploited by attackers, thereby converting the increased volume of AI-driven discoveries into a prioritized remediation strategy.

Trustpilot's collaboration with Bugcrowd in a recent "Ask Me Anything" webinar highlighted the evolving landscape of cybersecurity and the role of bug bounty programs in maintaining continuous security coverage. Traditional security tools like pen tests, EDR, and SAST scanners are deemed insufficient on their own due to their point-in-time nature, as opposed to the continuous assessment provided by a diverse pool of researchers in a bug bounty program. The discussion emphasized that vulnerabilities aren't always business-critical unless they impact what an organization values, such as trust in Trustpilot's case. Identity was identified as the most underrated attack surface, with mature organizations often exposed through API keys and CI/CD trust relationships. AI was acknowledged for its role in speeding up tasks like code reading and structuring findings, although it can fall short without proper validation and context. Trustpilot's initial struggles with a high volume of submissions highlighted the importance of transparency and efficient communication to keep elite researchers engaged, showcasing the necessity of integrating bug bounty programs with internal management and messaging tools for immediate response and feedback.

Savant Vista, a new feature of the Bugcrowd Platform, addresses the challenges of an expanding attack surface by providing continuous attack surface intelligence and proactive risk reduction for security teams. As organizations face issues from sprawl, shadow IT, and rapid development cycles, Savant Vista bridges the gap between asset discovery, exposure detection, and offensive testing, offering a unified view of assets and their vulnerabilities. It automates the mapping and monitoring of digital estates, enables scheduling of vulnerability scans based on asset criticality, and integrates seamlessly with human-led testing programs. The platform prioritizes real-world exploitability, helping security teams focus on reducing actual risk rather than merely managing vulnerabilities. By maintaining a comprehensive asset inventory and facilitating smart organization of assets, Savant Vista ensures visibility, validation, and prioritization, ultimately transforming security efforts from reactive to proactive measures.