AI Security

AWS Frontier Agents reached general availability on March 31, 2026, marking the most significant expansion of Amazon’s AI portfolio since Bedrock launched in 2023. Two production-ready agents — the AWS Security Agent and the AWS DevOps Agent — are now available to all AWS customers, backed by Amazon Bedrock and powered by Claude models from Anthropic. This review covers architecture, performance benchmarks, competitive positioning against Azure AI Agent Service and Google Cloud Agent Builder, and a practical deployment guide so you can get Frontier Agents running in your own pipeline today. ...

The threat surface for large language models has expanded beyond what most security teams anticipated three years ago. What began as a concern about chatbot misuse has evolved into a full-spectrum attack discipline targeting autonomous AI agents that browse the web, execute code, manage files, and call external APIs on behalf of users. This guide consolidates the current state of LLM red teaming as of 2026, covering the attack categories, specialized tooling, and operational processes that security teams need to protect AI-powered systems in production. ...

OpenAI acquiring PromptFoo is not a talent grab — it is a strategic acknowledgment that AI security testing is no longer optional infrastructure. With 93% of organizations now shipping AI-generated code and only 12% applying equivalent security standards, the attack surface is enormous and growing. PromptFoo was the most mature open-source tool purpose-built for LLM red-teaming, and OpenAI buying it means the company is betting that security evaluation needs to be a first-class part of the developer workflow, not an afterthought bolted on by a third-party CLI. ...

The best DAST tool for 2026 depends on your stack: Invicti leads on accuracy (99.98% proof-based), Bright Security is the top pick for AI/LLM app security with under 3% false positives, StackHawk wins for developer-centric CI/CD integration, and OWASP ZAP remains the strongest free option. This breakdown covers all ten. What Is DAST and Why AI Makes It Critical in 2026 Dynamic Application Security Testing (DAST) is the practice of probing a running application — sending real HTTP requests, manipulating inputs, and observing responses — to discover vulnerabilities that static analysis cannot find. Unlike SAST, which reads source code, DAST interacts with the app the same way an attacker would: through its live interfaces. In 2026, this matters more than ever because the DAST market was valued at USD 3.57 billion in 2025 and is projected to reach USD 11.02 billion by 2032 at a 17.5% CAGR, driven by API proliferation, AI-generated code vulnerabilities, and DevSecOps mandates. Only 44% of security teams currently use DAST tools despite the need being acute — which means the majority of organizations are shipping web apps and APIs without runtime security validation. ...

Cursor BugBot is an AI-powered code reviewer that automatically checks every pull request for real bugs and security vulnerabilities — not style issues or formatting complaints. It catches logic flaws, null-pointer errors, and CVEs inside PRs before they merge, with an 80% resolution rate and 2 million+ PRs reviewed per month as of 2026. What Is Cursor BugBot? (And Why It Matters in 2026) Cursor BugBot is an autonomous AI code reviewer built by the team behind the Cursor IDE, designed to detect actual bugs and security vulnerabilities in every pull request before they reach production. Unlike traditional linters that flag style violations and formatting inconsistencies, BugBot focuses exclusively on logic errors, race conditions, SQL injection vectors, and CVE-class vulnerabilities. By 2026, it processes over 2 million pull requests every month across 110,000+ enabled repositories — making it one of the most widely deployed AI review systems in production use. The timing matters: a January–April 2026 audit found that 92% of AI-built applications had critical security flaws, and 53% of AI-generated code ships with at least one vulnerability. BugBot fills the gap that emerges when teams ship faster using AI coding assistants but lack review bandwidth to manually scrutinize every change. It integrates directly with GitHub and surfaces comments inside PRs — no workflow changes required, no new dashboards to maintain. For teams already using Cursor’s IDE, BugBot represents a natural extension of the same AI-first philosophy into the review stage. ...