Silent Push, a company specializing in proactive cyber defense, has unveiled Silent Push 6.0, a significant upgrade to its cyber defense platform. The latest version is designed to help security teams act more quickly and efficiently through improved usability, enhanced visibility into threat infrastructure, and expanded integration capabilities. The release introduces upgrades to Traffic Origin and new workflow features that support a threat-informed security strategy focused on identifying and mitigating risks before attacks occur.

“Silent Push 6.0 is designed to cut through the noise and deliver actionable intelligence on adversary infrastructure before attacks materialize—something unmatched in the industry,” said Ken Bagnall, CEO and Co-Founder of Silent Push. “This release empowers enterprises and government organizations to identify emerging threats sooner, enabling informed decisions that strengthen cybersecurity defenses at the earliest stages of the attack lifecycle.”

The new platform enhancement is built to integrate seamlessly into existing security operations, helping teams focus on high-priority threats without requiring additional tools or major workflow changes.

Key Enhancements in Silent Push 6.0
Traffic Origin
A newly developed capability exclusive to Silent Push, Traffic Origin provides organizations with deeper visibility into malicious activity, infrastructure shifts, and traffic behavior to accurately identify the true geographic source of internet activity. The feature includes a dedicated user interface, access to a full year of historical data, and more granular permission controls. It supports a range of use cases, including fraud detection, Know Your Customer (KYC) verification, recruitment validation, and incident response investigations.

MCP Server Integration
Silent Push has introduced a hosted endpoint that allows its threat intelligence data to connect directly with AI platforms such as Claude, ChatGPT, and other large language models. Security analysts can conduct investigations using natural language queries, enabling tasks such as indicator enrichment, historical DNS analysis, infrastructure mapping, adversary clustering, risk assessment, and creation of investigative reports. By reducing unnecessary context and streamlining data access, the MCP Server helps accelerate investigations while lowering AI token consumption.

Redesigned Navigation and Module Structure
The platform now features three primary modules—Defend, Insight, and Reconnaissance—to simplify navigation and improve operational efficiency. Defend focuses on proactive integrations with SIEM, SOAR, firewall solutions, and Silent Push’s proprietary Indicators of Future Attack® (IOFA). Insight delivers comprehensive artifact context within a unified interface to speed up threat triage. Reconnaissance supports threat hunting and incident response teams by enabling infrastructure tracking and analysis. An additional module, Advanced Attribution, serves as the home for the Traffic Origin capability.

Enhanced TLP Amber Reports
Backend and infrastructure improvements have significantly increased report-loading performance. The updated reporting framework now supports richer content formats, including embedded video tutorials accessible directly within reports. Threat indicators referenced in reports can be explored further through pivoting capabilities, while the newly available TLP Amber Report API provides programmatic access to report metadata and related information.

Bulk Enrichment in Insight
The Bulk Enrichment feature enables analysts to evaluate multiple indicators simultaneously within a centralized dashboard. Designed for the early stages of investigations, it helps security teams quickly prioritize suspicious assets by providing immediate access to Silent Push intelligence. This capability addresses limitations commonly found in single-indicator lookup tools, allowing analysts to identify the most critical threats faster and more effectively.

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Valona Intelligence has unveiled its new Model Context Protocol (MCP) server, a solution designed to connect artificial intelligence platforms with external intelligence sources. As an open standard, MCP enables enterprise AI tools and agent frameworks—including Microsoft Copilot, Claude, and others—to access Valona's market and competitive intelligence directly within their workflows.

Artificial intelligence has become a standard component of modern business operations. According to McKinsey's 2026 research, nearly 90% of organizations now utilize AI technologies. However, as AI adoption becomes widespread, the differentiating factor is no longer access to the technology itself, but the quality and relevance of the information powering it.

"Organizations gain an advantage not from AI alone, but from the intelligence feeding those systems," said Stuart Reynish, Chief Product Officer at Valona. "Our MCP server allows enterprise AI platforms to draw upon continuously updated market and competitive insights. Rebuilding the same analysis repeatedly is both costly and inconsistent. Decision-making requires intelligence that is accurate, current, and immediately actionable."

The company believes that strategic decision-making is evolving from periodic research efforts to a model of continuous intelligence. Instead of requiring AI agents to generate analysis from raw information every time, Valona's MCP server provides access to a curated and constantly maintained intelligence foundation that is readily available whenever needed.

"The intelligence layer is the most challenging element to develop effectively, and we've spent more than twenty years refining it," said Eetu Laaksonen, Chief AI Officer at Valona. "MCP enables us to integrate that intelligence into the AI tools our customers already rely on, while also supporting the broader AI ecosystems they are building."

Laaksonen noted that interest in enterprise-wide intelligence is expanding beyond competitive market intelligence teams. "We're increasingly engaging with IT departments and senior executives because intelligence is becoming a strategic capability across the organization. Customers are telling us they want critical insights delivered proactively, rather than having to search for them."

Valona is currently working with a select group of enterprise customers to pilot the MCP server within Microsoft Copilot and agent-driven AI environments. The company plans to showcase the technology during its webinar, What Agentic AI Means for Competitive Intelligence, scheduled for June 24.

Artificial intelligence has rapidly become the go-to source for information, quietly replacing traditional search engines for many users — and most companies have yet to recognize the shift.

Today, millions of people consult AI tools such as ChatGPT, Claude, and Gemini before using conventional search platforms. Around half of consumers now prefer AI-driven answers over traditional search results, and those responses heavily influence purchasing choices, employment decisions, and brand trust. The impact extends even further: 94% of B2B buyers now rely on AI during purchasing decisions, while more than three-quarters of investors worldwide use AI-powered insights to guide investment strategies.

Despite this growing dependence on AI, many organizations still lack visibility into how their brands are represented in AI-generated responses. Are they appearing in results at all? If they are, is the portrayal accurate, balanced, or potentially damaging?

When existing tools failed to provide clear answers for clients, we decided to create a better solution.

“Communications leaders usually know their media coverage and search rankings, but very few understand how AI platforms currently describe their company,” said Charlie Wilkie. “That’s the visibility gap we designed this tool to solve.”

Introducing the AI Visibility Tracker from 3BL — a platform specifically created to measure and manage brand reputation within AI systems.

Key Features
Unlike many AI tracking tools focused mainly on product visibility, the AI Visibility Tracker concentrates on reputation — helping organizations understand how AI platforms interpret, discuss, and frame their brands.

The platform also delivers more advanced sentiment analysis than traditional tools. Instead of relying solely on positive or negative keywords, it evaluates the broader context of AI-generated discussions, capturing nuanced perceptions even when responses contain both praise and criticism.

“The foundation of public relations has always been that outside perspectives carry more weight than self-promotion,” Wilkie explained. “AI has amplified that reality even further, but many brands are still unprepared for it.”

As AI increasingly becomes the primary source of information for consumers, employees, investors, and business buyers, understanding how your brand appears in AI-generated content is no longer optional — it’s becoming a business necessity.

Click here to sign up to see your AI visibility score.