automation
Blind Trust in AI Creates Cybersecurity Risks
Allowing AI models to both interpret and execute commands without human oversight introduces significant cybersecurity vulnerabilities. This lack of critical review can lead to unintended consequences and security breaches.
Summer Staffing Shortages Expose IT Security Risks
Reduced IT staffing during summer vacation periods can create significant security vulnerabilities. Organizations are advised to leverage AI-driven automation to maintain consistent security operations and minimize reliance on manual processes, ensuring protection remains robust even with fewer personnel.
Threat Actors Uses Agentic AI to Rapidly Compromise Cloud Target
Researchers have identified threat actors leveraging agentic artificial intelligence to significantly speed up cloud compromises. What would typically take weeks of manual effort was accomplished in a mere 72 hours, demonstrating a new level of efficiency in cyberattacks.
Machine Speed, Human Judgement: How AI Changed the SOC in 2026
The article provides an inside perspective on how artificial intelligence and automation are reshaping security operations centers (SOCs). It highlights the integration of AI, automated processes, and agent-based workflows as key drivers of change in modern security.
Qualys Joins Cisco Cloud Control Studio as a Launch Partner to Bring Risk Intelligence to Agentic Operations
Qualys has partnered with Cisco to integrate its risk intelligence capabilities into Cisco's new Cloud Control Studio platform. This collaboration aims to provide joint customers with unified asset inventory, prioritized vulnerability findings, and automated remediation workflows directly within Cisco's AI-driven operational environment. The integration is designed to help security teams manage expanding attack surfaces and overwhelming alert volumes by providing context and enabling faster, more efficient responses.
Inside Elastic InfoSec's agentic SOC: cutting alert triage from 30 minutes to under 3
Elastic's InfoSec team has developed an automated security operations center (SOC) that significantly reduces alert triage time. By using deterministic queries and specialized AI agents, the system handles most alert investigations before human analysts are involved, cutting down a 30-minute process to under three minutes. This approach leverages Elastic's own technology stack and focuses on efficient, cost-effective automation to manage increasing alert volumes.
5 Myths About AI in the SOC Security Teams Need to Rethink
Security operations teams are increasingly adopting AI, but common assumptions about its role need reevaluation. Experts suggest AI should augment, not replace, human analysts by handling repetitive tasks and data processing. While automation is beneficial for enrichment and triage, critical actions still require human oversight. Transparency and explainability are crucial for building trust and ensuring analysts can confidently use AI outputs.
OpenClaw: risks for the users and how to mitigate them
OpenClaw, an AI agent ecosystem formerly known as Clawdbot and Moltbot, offers flexibility and task automation but introduces security risks to users and organizations. The system's 'skills' feature, which allows for natural language instructions and easy creation of extensions, can be exploited by attackers. The article aims to explore these security aspects, known vulnerabilities, and mitigation strategies.
From vulnerability report to CVE draft in minutes: how Elastic automated security advisories with AI
Elastic's InfoSec Product Security Team has developed an AI agent capable of generating comprehensive CVE security advisories. This agent utilizes generative AI and Retrieval-Augmented Generation (RAG) against MITRE's CWE and CAPEC databases, ensuring accurate classification and scoring. The process automates the drafting of advisories from raw vulnerability reports, significantly speeding up the disclosure phase.
AI Could Revolutionize Cybersecurity Analysis and Defense
A keynote speaker argued that cybersecurity is moving beyond its experimental phase due to increasing complexity and reliance on human attention. The speaker suggested that large language models offer a scalable solution by providing cheap, abundant evaluative power, enabling defenders to analyze and act more efficiently. This shift could lead to more automated, standardized, and sustainable security practices by integrating artificial intelligence with human expertise.