Breachlock is a leading global cyber security provider offering AI-powered Offensive Security Solutions for enterprises of all sizes. Before the LLM or Large Language Model revolution, artificial intelligence (AI) was already a big part of BreachLock’s technology. For close to five years now, BreachLock has been helping to solve offensive security use cases using AI to enhance outcomes.
However, while the interest in AI in cybersecurity remains high, humans continue to play a critical role. For example, BreachLock penetration testing services process data to solve large-scale problems for enterprises using automated algorithms and supervised NLP-based AI models. This still requires human intelligence to analyze repeatable patterns and render well-informed decisions about the test findings.
From the security engineers who design and implement machine learning systems, and analysts responsible for training models and enhancing their capabilities, to experts utilizing AI-generated data, it’s clear that humans and AI are closely intertwined as security technologies advance.
AI and Your Attack Surface
With modern enterprises relying heavily on external partnerships, regulatory bodies are increasingly requiring industries like financial services and critical infrastructure to assess risks beyond their own networks.
For example, the Digital Operational Resilience of the Financial Sector (DORA) broadens risk management requirements in the financial sector to include all external assets related to their partners, such as third, fourth, and even unknown parties, as well as services and infrastructure that could impact an enterprise’s operational resilience.
Thus, adopting a zero-scope approach to your attack surface has become more critical, as identifying the full range of both internal and external assets is not a task that can efficiently be handled by human effort alone. Relying on manual processes would be extremely costly, require more resources, and are more prone to error. Therefore, automation using AI and algorithmic discovery is the most effective way to map out the majority of an enterprise’s attack surface.
This highlights the fact that future security strategies will be closely integrated into AI-powered security solutions. One survey noted that nearly 1 in 3 enterprises consider AI to be a primary driver for their cybersecurity strategy moving forward but leaders are not prepared to trust this solely with AI.
According to some security leaders, there is concern whether this will make the situation worse. Security practitioners are already struggling with modern security tools and now security teams will also need to understand AI.
But humans play a pivotal role in contextualizing threats and data. AI and human engineers make a formidable team, but a lack of skilled experts presents obstacles to managing AI. This is one of the reasons that it is important for enterprises to work with security providers who truly understand how to use and integrate AI-powered tools and provide the skilled expertise needed to deliver the next generation of security solutions.
Using AI as a Force Multiplier for Attack Surface Management (ASM)
As attack surfaces expand and threats multiply, becoming more complex, faster, and more diverse, managing this is increasingly challenging, giving attackers a significant advantage. However, enterprises can harness AI in innovative ways to gain an edge in securing their attack surfaces.
This shift in AI has transformed the landscape of ASM where technologies, risks, and strategies converge with potentially severe consequences. For Chief Information Security Officers (CISOs), the reality is that AI has made the future of ASM more intricate and difficult to navigate.
Over the years, BreachLock has identified three big challenges in applying AI to cybersecurity, and until recently, no solution has fully addressed all of them. The challenges are:
- Enterprises often lack visibility into a significant portion of their IT assets, with many aware of only 70% of what they actually own.
- There has been a lack of integration between various data sources and cybersecurity tools, hindering the ability to create cohesive, comprehensive enterprise-wide views of security risk.
- Attackers are highly adaptable, frequently shifting tactics, which makes it difficult to accurately predict their attack methods and vectors they might target for compromise.
Any attempt to make ASM more efficient and effective has had to consider those three challenges.
The Role of AI in ASM
Fortunately, ASM can be enhanced by using AI. BreachLock’s AI-powered Offensive Security Solutions include Attack Surface Management (ASM), Penetration Testing as a Service (PTaaS), Cloud Security Posture Management (CSPM), SaaS Security Posture Management (SSPM), and External Attack Surface Management (EASM) for Dark Web exposure.
BreachLock’s AI technology offers numerous benefits for these solutions and specifically ASM, including automation, scalability, performance (at scale), accuracy, precision, and 100% visibility. It is a powerful, efficient, and reliable force multiplier for BreachLock security testing teams, technologies, and ASM-directed processes.
Looking Ahead: Redefining ASM
BreachLock AI-powered technology and Offensive Security solutions cover asset analysis, attack surface reduction, continuous threat monitoring, and risk management, identifying vulnerabilities from an attacker’s perspective.
Human intelligence and expertise analyze repeatable patterns to render well-informed decisions about test findings. With real-time monitoring and AI-driven recommendations, BreachLock helps enterprises to focus on the most critical risk vectors, ensuring they are one step ahead of the next potential attack.
CISOs and security teams must continue to anticipate what attackers will do next. It is essential that enterprises have the right strategies, tools, and processes in place to prevent future attacks. However, it is not enough to rely solely on innovative technology, as a more strategic approach is required. CISOs, in collaboration with C-suite leaders and boards, must foster a proactive mindset across the entire enterprise.
Attack Surface Management has emerged as a necessity and AI has become a powerful ally. By leveraging AI expertise, enterprises can tap into its capabilities to transform their ASM approaches. With mission-critical assets at stake, this is the time for fresh perspectives and creative solutions to stay ahead of evolving threats.
