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Cybersecurity Defences Employing AI Can Combat Threats with Greater Speeds

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Emile Abou Saleh, the Senior Director for Middle East, Turkey and Africa at Proofpoint, says a proactive approach to cybersecurity robustly protects organizations against a wide range of threats in an increasingly complex digital landscape

What have we achieved so far in terms of use case scenarios of Gen AI in the realm of cybersecurity?
Generative AI has gained considerable attention in the news lately, and like any new technology, there’s a lot of excitement around it. Today’s Generative AI tools go beyond traditional chatbots; they are becoming more advanced. Generative AI’s potential reaches far and wide, benefiting professionals across different industries. Financial advisers can use it to analyze market trends, educators can tailor lessons to students’ needs, and it’s also proving useful in the field of cybersecurity. Security analysts can leverage Generative AI to examine user behaviour and detect patterns that could indicate potential data breaches.

One of the standout features of Generative AI in cybersecurity is its ability to quickly and accurately process vast amounts of data related to emerging threats. Security administrators can use these tools to run queries quickly, and in just a few minutes, these tools can summarize current credential compromise threats and highlight specific indicators to watch out for.

Why according to you should cybersecurity companies leverage generative AI?
Our lives and work cultures are forever changed, with so many people working and interacting digitally—and the velocity of business and the volume of corporate data we generate growing exponentially, across multiple digital platforms.

Many organizations across all industries have found that implementing artificial intelligence (AI) into business systems has helped them to ensure continuity, with one main aspect being increased productivity. When looking at this from a cybersecurity point of view, there are many ways AI and machine learning (ML) can bolster an organization’s overall cybersecurity posture.

Today’s threat landscape is characterized by attackers preying on human vulnerability. Proofpoint research shows that nearly 99% of all threats require some sort of human interaction. Whether it is malware-free threats such as the different types of Business Email Compromise (BEC) or Email Account Compromise (EAC) like payroll diversion, account takeover, and executive impersonation, or malware-based threats, people are falling victim to these attacks day-in and day-out. And all it takes is one click, from one employee for a threat actor to infiltrate an organization’s systems, no matter how complex the environment.

To stop these types of attacks, organizations need to deploy a security solution that can stay ahead of the ever-changing landscape and adapt to the way humans act. AI and ML are critical components in a robust cybersecurity detection strategy. It’s faster and more effective than manual analysis and can quickly adapt to new and evolving threats and trends. Cybersecurity defences that employ AI can combat such threats with greater speed, relying on data and learnings from previous, similar attacks to predict and prevent their spread.

What are the cybersecurity challenges facing companies with the adoption of AI and how can they be overcome?
With the adoption of AI, organizations face a set of cybersecurity challenges that need immediate attention. While AI has shown remarkable progress in defending against common threats, it has also opened doors for cybercriminals.

Take phishing: AI has the potential to supercharge this threat, increasing the speed and accuracy in which these phishing emails are sent to victims. However, it’s important to remember that many social engineering emails aren’t designed to be “perfect” – they are intentionally written poorly to find people who are more likely to engage.

That’s also only one part of the threat. Headers, senders, attachments, and URLs are among the many other threat indicators that are analyzed by robust detection technologies. Even where there would be a substantial benefit to having better-crafted emails, like many business email compromise scenarios, there is a lot of other information the threat actor needs to have access to. They need to know who is paying what money to whom and at what dates, which they probably have already accessed in a different way. They don’t necessarily need AI assistance when they already have access to that person’s inbox and they can merely copy an old email.

It’s crucial for organizations to note that no matter the attack vector, or how complex it is, the majority of cyberattacks require human interaction to be successful. By tricking just one employee, threat actors can circumvent security tools and siphon sensitive corporate data. Organizations must implement a people-centric cybersecurity strategy, consistently training employees at all levels of the business, in cybersecurity best practices so they are aware of the latest cyber threats and are able to detect them, report them, and not fall victim to them.

How can organizations use their resources effectively to leverage Gen AI to gain a competitive edge in the cybersecurity landscape?
To effectively leverage Generative AI and gain a competitive advantage in the cybersecurity landscape, organizations should focus on two vital aspects. It is firstly essential to embrace a people-centric security model for data loss prevention, acknowledging that individuals often play a pivotal role in the movement of data. This approach encompasses content awareness, behavioural analysis, and threat awareness, granting in-depth insights into how employees interact with sensitive data.

Increased visibility facilitates real-time detection and prevention of data loss incidents. Secondly, organizations should integrate artificial intelligence (AI) and machine learning (ML) technologies into their cybersecurity practices. For instance, in email security solutions, AI and ML swiftly identify and thwart phishing campaigns, malicious URLs, imposter messages, and unusual user activity in cloud accounts. A proactive approach to cybersecurity robustly protects organizations against a wide range of threats in an increasingly complex digital landscape.

Artificial Intelligence

CyberKnight Partners with Ridge Security for AI-Powered Security Validation

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The automated penetration testing market was valued at roughly $3.1 billion in 2023 and is projected to grow rapidly, with forecasts estimating a compound annual growth rate (CAGR) between 21% and 25%. By 2030, the sector is expected to reach approximately $9 to $10 billion. The broader penetration testing industry is also expanding, with projections indicating it will surpass $5.3 billion by 2027, according to MarketandMarket.

To support enterprises and government entities across the Middle East, Turkey and Africa (META) with identifying and validating vulnerabilities and reducing security gaps in real-time, CyberKnight has partnered with Ridge Security, the World’s First Al-powered Offensive Security Validation Platform. Ridge Security’s products incorporate advanced artificial intelligence to deliver security validation through automated penetration testing and breach and attack simulations.

RidgeBot uses advanced AI to autonomously perform multi-vector iterative attacks, conduct continuous penetration testing, and validate vulnerabilities with zero false positives. RidgeBot has been deployed by customers worldwide as a key element of their journey to evolve from traditional vulnerability management to Continuous Threat Exposure Management (CTEM).

“Ridge Security’s core strength lies in delivering holistic, AI-driven security validation that enables organizations to proactively manage risk and improve operational performance,” said Hom Bahmanyar, Chief Enablement Officer at Ridge Security. “We are delighted to partner with CyberKnight to leverage their network of strategic partners, deep-rooted customer relations, and security expertise to accelerate our expansion plans in the region.”

“Our partnership with Ridge Security is a timely and strategic step, as 69% of organizations are now adopting AI-driven security for threat detection and prevention,” added Wael Jaber, Chief Strategy Officer at CyberKnight. “By joining forces, we enhance our ability to deliver automated, intelligent security validation solutions, reaffirming our commitment to empowering customers with resilient, future-ready cybersecurity across the region.”

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Artificial Intelligence

Cequence Intros Security Layer to Protect Agentic AI Interactions

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Cequence Security has announced significant enhancements to its Unified API Protection (UAP) platform to deliver a comprehensive security solution for agentic AI development, usage, and connectivity. This enhancement empowers organizations to secure every AI agent interaction, regardless of the development framework. By implementing robust guardrails, the solution protects both enterprise-hosted AI applications and external AI APIs, preventing sensitive data exfiltration through business logic abuse and ensuring regulatory compliance.

There is no AI without APIs, and the rapid growth of agentic AI applications has amplified concerns about securing sensitive data during their interactions. These AI-driven exchanges can inadvertently expose internal systems, create significant vulnerabilities, and jeopardize valuable data assets. Recognising this critical challenge, Cequence has expanded its UAP platform, introducing an enhanced security layer to govern interactions between AI agents and backend services specifically. This new layer of security enables customers to detect and prevent AI bots such as ChatGPT from OpenAI and Perplexity from harvesting organizational data.

Internal telemetry across Global 2000 deployments shows that the overwhelming majority of AI-related bot traffic, nearly 88%, originates from large language model infrastructure, with most requests obfuscated behind generic or unidentified user agents. Less than 4% of this traffic is transparently attributed to bots like GPTBot or Gemini. Over 97% of it comes from U.S.-based IP addresses, highlighting the concentration of risk in North American enterprises. Cequence’s ability to detect and govern this traffic in real time, despite the lack of clear identifiers, reinforces the platform’s unmatched readiness for securing agentic AI in the wild.

Key enhancements to Cequence’s UAP platform include:

  • Block unauthorized AI data harvesting: Understanding that external AI often seeks to learn by broadly collecting data without obtaining permission, Cequence provides organizations with the critical capability to manage which AI, if any, can interact with their proprietary information.
  • Detect and prevent sensitive data exposure: Empowers organizations to effectively detect and prevent sensitive data exposure across all forms of agentic AI. This includes safeguarding against external AI harvesting attempts and securing data within internal AI applications. The platform’s intelligent analysis automatically differentiates between legitimate data access during normal application usage and anomalous activities signaling sensitive data exfiltration, ensuring comprehensive protection against AI-related data loss.
  • Discover and manage shadow AI: Automatically discovers and classifies APIs from agentic AI tools like Microsoft Copilot and Salesforce Agentforce, presenting a unified view alongside customers’ internal and third-party APIs. This comprehensive visibility empowers organizations to easily manage these interactions and effectively detect and block sensitive data leaks, whether from external AI harvesting or internal AI usage.
  • Seamless integration: Integrates easily into DevOps frameworks for discovering internal AI applications and generates OpenAPI specifications that detail API schemas and security mechanisms, including strong authentication and security policies. Cequence delivers powerful protection without relying on third-party tools, while seamlessly integrating with the customer’s existing cybersecurity ecosystem. This simplifies management and security enforcement.

“Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomously. We’ve taken immediate action to extend our market-leading API security and bot management capabilities,” said Ameya Talwalkar, CEO of Cequence. “Agentic AI introduces a new layer of complexity, where every agent behaves like a bidirectional API. That’s our wheelhouse. Our platform helps organizations embrace innovation at scale without sacrificing governance, compliance, or control.”

These extended capabilities will be generally available in June.

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Fortinet Expands FortiAI Across its Security Fabric Platform

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Fortinet has announced major upgrades to FortiAI, integrating advanced AI capabilities across its Security Fabric platform to combat evolving threats, automate security tasks, and protect AI systems from cyber risks. As cybercriminals increasingly weaponize AI to launch sophisticated attacks, organizations need smarter defenses. Fortinet—with 500+ AI patents and 15 years of AI innovation—now embeds FortiAI across its platform to:

  • Stop AI-powered threats
  • Automate security and network operations
  • Secure AI tools used by businesses

“Fortinet’s AI advantage stems from the breadth and depth of our AI ecosystem—shaped by over a decade of AI innovation and reinforced by more patents than any other cybersecurity vendor,” said Michael Xie, Founder, President, and Chief Technology Officer at Fortinet. “By embedding FortiAI across the Fortinet Security Fabric platform, including new agentic AI capabilities, we’re empowering our customers to reduce the workload on their security and network analysts while improving the efficiency, speed, and accuracy of their security and networking operations. In parallel, we’ve added coverage across the Fabric ecosystem to enable customers to monitor and control the use of GenAI-enabled services within their organization.”

Key upgrades:
FortiAI-Assist – AI That Works for You

  1. Automatic Network Fixes: AI configures, validates, and troubleshoots network issues without human help.
  2. Smarter Security Alerts: Cuts through noise, prioritizing only critical threats.
  3. AI-Powered Threat Hunting: Scans for hidden risks and traces attack origins.

FortiAI-Protect – Defending Against AI Threats

  1. Tracks 6,500+ AI apps, blocking risky or unauthorized usage.
  2. Stops new malware with machine learning.
  3. Adapts to new attack methods in real time.

FortiAI-SecureAI – Safe AI Adoption

  1. Protects AI models, data, and cloud workloads.
  2. Prevents leaks from tools like ChatGPT.
  3. Enforces zero-trust access for AI systems.

FortiAI processes queries locally, ensuring sensitive data never leaves your network.

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