Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

appknox

Ensuring API Testing Meets Compliance: Policies, Performance, and Proof

Dec 23, 2025 By Rucha Wele In Appknox
APIs sit at the center of modern applications. They move data between systems, power mobile apps, and enable integrations at scale. Naturally, they are also a focal point for regulators, auditors, and attackers. Most organizations today do test their APIs. Yet many still struggle during audits. Not because testing didn’t happen, but because it wasn’t consistent, governed, or provable. Compliance frameworks don’t ask whether you ran an API scan.
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Best Practices for Enterprise macOS Security: Tools, Techniques, and Detection Strategies

Best Practices for Enterprise macOS Security: Tools, Techniques, and Detection Strategies

Dec 23, 2025 By SecuritySenses In SecuritySenses
macOS data is increasingly targeted by hackers due to the sensitive information that Macs hold. Users require strong Mac cybersecurity measures to protect themselves from attacks. Combining Mac's built-in security features with third-party solutions provides hardened protection and continuous detection. Endpoint security for Mac best practices improve your enterprise macOS security. Implement secure configurations, effective device management, and real-time detection for advanced protection. Using a multi-protection strategy increases recovery speed and reduces the attack surface.
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Asymmetric Data: The New Challenge for API Security

Dec 22, 2025 By A10 Networks In A10 Networks
Asymmetric Data: The New Challenge for API Security In this A10 Networks video, "APIs are the Language of AI: Protecting Them is Critical," security experts Jamison Utter and Carlo Alpuerto discuss the unique challenges of securing AI-driven data exchanges. Unlike traditional API interactions—where a request for a video clearly results in a video—AI interactions are defined by a "phenomenal" level of asymmetry. A tiny text request can trigger a massive, unpredictable response, making traditional security prediction models nearly obsolete.
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Snyk

From Code to Agents: Proactively Securing AI-Native Apps with Cursor and Snyk

Dec 22, 2025 By Manoj Nair In Snyk
The rapid adoption of AI agents for development is creating a critical security gap. We are moving from predictable logic, deterministic code paths, and human-driven workflows to non-deterministic agents that reason, plan, and act autonomously using large language models across the broader software development lifecycle. As enterprises adopt these autonomous AI agents, the core challenge isn’t just the new risks and attack vectors; it’s a loss of runtime control.
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CrowdStrike

How CrowdStrike Trains GenAI Models at Scale Using Distributed Computing

Dec 22, 2025 By Andrei Preda - Alexandru Dinu - Florian Stortz - Nathan Nusaputra - Catalin-Andrei Stan In CrowdStrike
Large language models (LLMs) have revolutionized artificial intelligence and are rapidly transforming the cybersecurity landscape. As these powerful models become commonly used among both attackers and defenders, developing specialized cybersecurity LLMs has become a strategic imperative. The CrowdStrike 2025 Global Threat Report highlights a concerning trend: Threat actors are increasingly enhancing social engineering and computer network operations campaigns with LLM capabilities.
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Zenity

Zenity 2025 Year in Review: Building AI Security for the Enterprise

Dec 22, 2025 By Greg Zemlin In Zenity
For security teams, the adoption of agents showed up operationally before it showed up strategically - creating new expectations and requirements. Risk is no longer tied to prompts or the model alone. It shows up in what agents do once they are connected to critical systems - coming from permissions they inherit, tools they invoke, and data they move.
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