Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Secure AI Written Code Before It Ships: Salt Code

AI coding assistants are transforming how enterprise software gets built. Developers at every level are prompting their way to production-ready APIs, MCP integrations, and agentic workflows faster than any security team can review them. The problem is that none of those assistants knows your internal security standards, regulatory obligations, or risk tolerance. The result is insecure patterns shipping unnoticed, vulnerabilities discovered downstream when fixes are costly, and compliance becoming a guessing game on every commit.

What is Security Posture Management and Why is it Important?

Modern organizations don't operate from a single server room anymore. Today's enterprise environment spans dozens of cloud services, SaaS applications, APIs, AI agents, and non-human identities, all of which are continuously changing. A quarterly security audit is no longer a safety net, but now considered a gap.

Guide to Agentic AI Governance

Agentic AI governance is about keeping powerful, autonomous AI systems aligned, safe, and accountable as they act on our behalf. It’s now a certainty that AI agents will be deployed enterprise-wide. So, we need to look more deeply into those agents, figure out where they are, how to find them, and fully understand what they are doing in deployment so we can prevent attacks. The most dangerous agentic attacks will not look like attacks at the layer where they originate.

Salt Debuts First AWS WAF Managed Ruleset for AI Agent and API Protection

Your WAF is doing its job. It's blocking SQLi, XSS, and the usual suspects. But here's the problem: it wasn't built for APIs, and it definitely wasn't built for AI agents. APIs now power nearly every digital experience. And AI agents — the automated systems that access your APIs at machine speed, at machine scale — are the fastest-growing source of that traffic.

Top Security Risks of AI Agents

AI agents are rapidly moving from experimental projects into everyday business operations. Unlike traditional AI systems that generate content or answer questions, AI agents can take action. They can call APIs, access applications, retrieve data, execute workflows, and make decisions with limited human intervention. That shift is creating a new security challenge for enterprises.

The EU AI Act: Compliance for Companies Serving the EU Market

The EU AI Act is a global business issue. Just like GDPR before it, it reaches beyond EU borders. If your organization does business in the EU, you are in scope. Full enforcement begins August 2, 2026, with fines of up to 35 million euros or 7% of global turnover for non-compliance.

The Hugging Face Incident Proved the Real AI Risk Is in the Action Layer

Last week, an AI system crossed a line many still considered theoretical. During an internal cybersecurity evaluation, OpenAI tested a combination of models, including GPT-5.6 Sol and a more capable pre-release model, on ExploitGym, a benchmark that measures whether agents can turn software vulnerabilities into working exploits. The models were run with reduced cyber refusals and without the production classifiers normally used to prevent high-risk cyber activity.

Understanding the Importance of MCP Security

AI agents are moving from experiments into production workflows, and the Model Context Protocol (MCP) is becoming the connective layer that enables those agents to access enterprise data, applications, APIs, repositories, and automation tools. That makes MCP powerful, but also security-critical. As organizations adopt agentic AI, they need to understand not only how MCP improves connectivity but also how it creates new visibility, governance, and attack-surface challenges.