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Artificial Intelligence

Cloudflare Launches Tool to Block AI Bots

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Cloud service giant Cloudflare is taking a stand against rogue AI bots scraping website data for training models. Their newly launched, free tool aims to combat this growing problem. The issue lies with some AI vendors, like Google, OpenAI, and Apple, who allow website owners to block data-scraping bots through robots.txt files. However, as Cloudflare points out, these blockers are often ignored, leaving website owners vulnerable.

To address this, Cloudflare has developed advanced bot detection models specifically trained to identify AI bots. These models analyze traffic patterns and behaviour, including attempts to mimic human web browsing activity. This allows them to catch even the most cunning scraper bots. Cloudflare has also implemented a reporting system for website owners to flag suspected AI bots and crawlers. They plan to continuously update their blacklist based on user reports and manual investigations.

The rise of powerful generative AI models has fueled a massive demand for training data. This has led to a surge in AI scraper bots, often operating without permission or compensation for the data they collect. Many websites are opting to block these bots entirely. Studies show a significant number of top websites blocking bots used by leading AI companies. However, some vendors seem to disregard these blockers, prioritizing data collection over user consent.

Blocking all bots can have unintended consequences. Some AI tools, like Google’s AI Overviews, exclude websites that block specific crawlers. This can limit valuable referral traffic for website owners. Cloudflare’s tool offers a potential solution, but its effectiveness hinges on the accurate detection of these clandestine AI bots. The ongoing battle between website owners and AI companies highlights the need for a clearer regulatory framework to govern data collection practices in the AI training landscape.

Artificial Intelligence

As Adversarial GenAI Takes Off, Threat Intel Must Modernize

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Written by Bart Lenaerts, Senior Product Marketing Manager, Infoblox (more…)

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Artificial Intelligence

Help AG and F5 Collaborate on Managed App and API Security

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Help AG, the cybersecurity arm of e& enterprise, has become the first Managed Services Provider (MSP) partner for F5 in the Middle East. Building on their existing relationship, Help AG is now offering a new Managed App and API Protection Service based on the F5 Distributed Cloud Platform. This service is designed to provide continuous, cloud-delivered security for modern digital systems, including those in public, private, edge, and hybrid cloud environments.

Today’s threat landscape is increasingly complex. As businesses move towards API-driven architectures, edge computing, and cloud-native applications, they expose a wider attack surface. Security teams face growing pressure from automated bot attacks, API misuse, and sophisticated Distributed Denial of Service (DDoS) attempts. Many organizations also lack the necessary knowledge and tools to defend against these attacks effectively.

Help AG’s new service directly addresses these challenges. It offers multi-layered protection as a managed, Software-as-a-Service (SaaS) solution. The service uses F5’s globally recognized Distributed Cloud Services and is operated 24/7 by Help AG’s expert Security Operations Center (SOC) team. This allows clients to streamline operations, meet compliance requirements, and respond to threats in real time. Businesses can now deploy resilient, compliant, and cost-efficient application protection, backed by Help AG’s local expertise.

Stephan Berner, CEO of Help AG, stated, “This partnership with F5 is a major step forward for enterprise security. It reflects our shared goal of securing every application, API, and digital interaction at scale. This new service provides regional organizations with enterprise-grade security that is proactive, cost-effective, and built for the cloud-first era.”

The new solution offers unified protection that includes Web Application Firewall (WAF), advanced bot mitigation, API discovery and security, and DDoS defense. All these features are managed through a centralized SaaS-based console, providing full visibility and control. Clients also benefit from flexible deployment options across various locations and continuous support and tuning from Help AG’s expert teams.

Mustapha Hlil, Director of Channel Sales for the Middle East, Türkiye and Africa at F5, commented, “As cyber threats grow more sophisticated, the need for always-on, adaptable security is critical. Help AG’s security expertise, managed services leadership, and 24/7 SOC support, combined with the F5 Distributed Cloud platform, offer a powerful solution. This will greatly help enterprises that lack the in-house expertise to deploy and manage security solutions.”

This launch marks a new phase in the Help AG and F5 partnership, reinforcing their commitment to securing the region’s digital future and helping organizations build trust in their digital interactions.

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Artificial Intelligence

Cloud Security Trade-Offs Rise: 91% of Leaders Face AI Threats

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Gigamon has released its 2025 Hybrid Cloud Security Survey, revealing that hybrid cloud infrastructure is under mounting strain from the growing influence of artificial intelligence (AI). The annual study, now in its third year, surveyed over 1,000 global Security and IT leaders across the globe. As cyberthreats increase in both scale and sophistication, breach rates have surged to 55 percent during the past year, representing a 17 percent year-on-year (YoY) rise, with AI-generated attacks emerging as a key driver of this growth.

Security and IT teams are being pushed to a breaking point, with the economic cost of cybercrime now estimated at $3 trillion worldwide according to the World Economic Forum. As AI-enabled adversaries grow more agile, organizations are challenged with ineffective and inefficient tools, fragmented cloud environments, and limited intelligence.

Key findings highlight how ai is reshaping hybrid cloud security priorities:

  • AI’s role in escalating network complexity and accelerating risk is evident. The study reveals that 46 percent of Security and IT leaders say managing AI-generated threats is now their top security priority. One in three organizations report that network data volumes have more than doubled in the past two years due to AI workloads, while nearly half of all respondents (47 percent) are seeing a rise in attacks targeting their organization’s large language model (LLM) deployments. More than half (58 percent) say they’ve seen a surge in AI-powered ransomware—up from 41 percent in 2024 underscoring how adversaries are exploiting AI to outpace and outflank existing defenses.
  • Compromises highlight continued trade-offs in foundational areas of hybrid cloud security. Nine out of ten (91 percent) Security and IT leaders concede to making compromises in securing and managing their hybrid cloud infrastructure. The key challenges that create these compromises include the lack of clean, high-quality data to support secure AI workload deployment (46 percent) and lack of comprehensive insight and visibility across their environments, including lateral movement in East-West traffic (47 percent).
  • Public cloud risks prompt industry recalibration. Once considered an acceptable risk in the rush to scale post-COVID operations, the public cloud is now coming under increasingly intense scrutiny. Many organizations are rethinking their cloud strategies in the face of their growing exposure, with 70 percent of Security and IT leaders now viewing the public cloud as a greater risk than any other environment. As a result, 70 percent report their organization is actively considering repatriating data from public to private cloud due to security concerns and 54 percent are reluctant to use AI in public cloud environments, citing fears around intellectual property protection.
  • Visibility is top of mind for security leaders. As cyberattacks become more sophisticated, the limitations of existing security tools are coming sharply into focus. Organizations are shifting their priorities toward gaining complete visibility into their environments, a capability now seen as crucial for effective threat detection and response. More than half (55 percent) of respondents lack confidence in their current tools’ ability to detect breaches, citing limited visibility as the core issue. As a result, 64 percent say their number one focus for the next 12 months is achieving real-time threat monitoring delivered through having complete visibility into all data in motion.

With AI driving unprecedented traffic volumes, risk, and complexity, nearly nine in 10 (89 percent) Security and IT leaders cite deep observability as fundamental to securing and managing hybrid cloud infrastructure. Executive leadership is taking notice, as boards increasingly prioritize complete visibility into all data in motion, with 83 percent confirming that deep observability is now being discussed at the board level to better protect hybrid cloud environments.

“Security teams are struggling to keep pace with the speed of AI adoption and the growing complexity and vulnerability of public cloud environments,” said Mark Jow, technical evangelist, EMEA, at Gigamon. “Deep observability addresses this challenge by combining MELT data with network-derived telemetry such as packets, flows, and metadata, delivering increased visibility and amore informed view of risk. It enables teams to eliminate visibility gaps, regain control, and act proactively with increased confidence. With 88 percent of Security and IT leaders agreeing it is critical to securing AI deployments, deep observability is fast becoming a strategic imperative.”

“With nearly half of organizations saying attackers are already targeting their large language models, AI security can’t be an afterthought, it needs to be a top priority,” said Mark Walmsley, CISO at Freshfields. “The key to staying ahead? Visibility. When we can clearly see what’s happening across AI systems and data flows, we can cut through the noise and manage risk more effectively. Deep observability helps us spot vulnerabilities early and put the right protections in place before issues arise.”

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