Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Introducing Forward AI

Jan 29, 2026 By Forward Networks In Forward Networks
The Network is Complex. Operating It Shouldn't Be. Forward AI transforms network operations by reducing manual analysis, expert dependency, and guesswork. By combining conversational interaction with a mathematically accurate digital twin, teams can validate intent, understand actual network behavior, and act with confidence across even the most complex environments.
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gitguardian

OpenClaw (Moltbot) Personal Assistant Goes Viral - And So Do Your Secrets

Jan 29, 2026 By Guillaume Valadon In GitGuardian
Early 2026, Moltbot a new AI personal assistant went viral. GitGuardian detected 200+ leaked secrets related to it, including from healthcare and fintech companies. Our contribution to Moltbot: a skill that turns secret scanning into a conversational prompt, letting users ask "is this safe?".
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LimaCharlie

Threat hunting to detection engineering: Analyzing real malware with Claude Code, LimaCharlie, and Linux

Jan 29, 2026 By LimaCharlie In LimaCharlie
Claude Code, originally just auto-complete on steroids for IDEs, shows a lot of promise for becoming a major tool in the DFIR/detection engineering/security analyst’s toolbox. Whether it’s Claude Code’s support of MCP, agent skills, or general ability to quickly figure out how to accomplish a given task, it is rapidly becoming more than a code generation tool. This is the first of a three-part series.
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appknox

Vibe Coding Speeds Up Mobile Apps But Creates New Security Risks

Jan 29, 2026 By Ginil P G In Appknox
AI-assisted development has crossed a tipping point. Mobile teams are no longer debating whether to use AI to write code. They are deciding how fast they can ship with it. This shift, often called vibe coding, prioritizes intent and speed over manual implementation. Developers describe what they want, and AI fills in the rest. Velocity improves. Releases accelerate. But security assumptions quietly break. For mobile applications, that risk compounds.
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Episode 7 - Practical AI for Zeek, MITRE, and Security Docs

Jan 29, 2026 By Corelight In Corelight
In Episode 7 of Corelight DefeNDRs, join me, Richard Bejtlich, as I sit down with Dr. Keith Jones, Corelight's principal security researcher, to discuss the practical applications of AI in enhancing network security. We delve into how large language models (LLMs) can assist in cleaning up documentation and generating Zeek scripts, sharing insights from our extensive experience in incident response and coding. Keith reveals the challenges and successes he has encountered using LLMs to streamline processes, including their role in analyzing MITRE techniques.
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cloudflare

Introducing Moltworker: a self-hosted personal AI agent, minus the minis

Jan 29, 2026 By Celso Martinho In Cloudflare
The Internet woke up this week to a flood of people buying Mac minis to run Moltbot (formerly Clawdbot), an open-source, self-hosted AI agent designed to act as a personal assistant. Moltbot runs in the background on a user's own hardware, has a sizable and growing list of integrations for chat applications, AI models, and other popular tools, and can be controlled remotely. Moltbot can help you with your finances, social media, organize your day — all through your favorite messaging app.
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salt security

Measuring Agentic AI Posture: A New Metric for CISOs

Jan 29, 2026 By Eric Schwake In Salt Security
In cybersecurity, we live by our metrics. We measure Mean Time to Respond (MTTR), Dwell Time, and Patch Cadence. These numbers indicate to the Board how quickly we respond when issues arise. But in the era of Agentic AI, reaction speed is no longer enough. When an AI Agent or an MCP server is compromised, data exfiltration happens in milliseconds rather than days. If you are waiting for an incident to measure your success, you have already lost.
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nightfall

Beyond Pattern Matching: How AI-Native File Classification Solves Modern DLP Challenges

Jan 29, 2026 By Chris Martinez In Nightfall
Legacy DLP operates on a fundamental constraint: it identifies sensitive data by matching patterns. Credit card numbers follow the Luhn algorithm. Social Security numbers conform to a nine-digit format. API keys match specific string patterns. This approach works for structured data, but it fails to address a critical reality: Your most sensitive assets aren't numbers. They're documents.
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upguard

Productivity at a Price: The Rising Cost of AI Convenience

Jan 28, 2026 By Shane Moosa In UpGuard
Humans have always sought to streamline productivity through the most convenient solutions available, prioritizing speed to stay ahead and gain an edge over the competition. From the assembly line to the cloud, the goal remains the same: do more with less friction. Today, that convenience is synonymous with AI. While these tools have revolutionized how we work, the reality remains that rapid innovation always comes with a hidden cost.
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Tines

Voice of Security 2026: AI is everywhere yet manual work persists

Jan 28, 2026 By Thomas Kinsella In Tines
AI adoption in security has soared. But for many teams, manual work and burnout remain stubbornly high. To understand why, and what security teams must do next, we partnered with Sapio research to survey more than 1,800 security leaders and practitioners worldwide for our Voice of Security 2026 report. We wanted to learn how teams are using AI and automation, how the role of security is evolving, and how professionals believe AI will impact their careers. The data is revealing.
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