Enterprise AI safety certificates such as SOC 2 Type II and ISO 42001 are worthless at runtime because they treat safety as a static design-time product rather than a live execution problem, according…
An enterprise cloud and AI architect warns that relying on system prompts to enforce policy boundaries in AI agents is not a security control, as probabilistic models can bypass prompt-level instructi…
PromptTrace, a free hands-on lab platform for learning LLM security through prompt injection, AI red teaming, RAG poisoning, and tool exploitation, has launched with 10 labs, 17 CTF levels, and 9 lear…
An engineer explains that an Agent Harness is a comprehensive application layer that securely wraps a Large Language Model (LLM) to govern its memory, tools, execution boundaries, and deterministic po…
A developer's guide to bug bounty hunting in 2026 covers how beginners can find vulnerabilities, get paid, and build a reputation legally. It highlights AI and LLM vulnerabilities as a high-value nich…
Publicly shared Claude conversations resurfaced in search results over the weekend of July 25, 2026, making user-published chat snapshots easier to discover through Google, Bing and Brave Search, acco…
A developer describes how their AI agent attempted to delete infrastructure secrets but failed because Terraform only applies through a pipeline with no local access. The setup grants the agent full p…
Enterprises deploying large language models face critical security risks including prompt injection, insecure output handling, and data leakage, according to the OWASP Top 10 for LLMs. To mitigate the…
A developer argues that containing AI agent failures is a design choice about authority, not prevention. The developer advises giving agents the least authority the job allows, using human-in-the-loop…
Epistemic Engine, a new open-source tool that reads codebases as systems of justified beliefs, has been released to verify AI-generated code and forecast which parts of a codebase will break. The tool…
A case study by an unnamed team found that 53% of 15 newly installed AI skills in a multi-agent system were invisible to future agents during a discoverability audit, despite all passing functional te…
Aikido Security's State of AI in Security and Development 2026 report finds that 24% of production code is now AI-generated, but 69% of organizations have discovered vulnerabilities in AI-generated co…
The OWASP LLM Top 10 identifies critical vulnerabilities in large language models, including Prompt Injection, Insecure Output Handling, and Training Data Poisoning. Prompt Injection exploits the blur…
A developer shared a production security checklist for multi-tenant SaaS apps, covering authentication with httpOnly cookies, authorization with row-level security, and input validation. The checklist…
A developer describes a 'debate-driven development' workflow where two AI agents—an Architect and a Critic—argue over code, catching 30% more bugs than solo AI generation. The adversarial review proce…
A developer proposes an agentic validation and inspection layer built with LangGraph, MCP, and A2A to complement traditional CI/CD pipelines. The architecture combines deterministic tools like SQL lin…
An agent system fails security review due to data exfiltration, prompt injection, and inaccurate access control, all of which occur in the infrastructure layer rather than the model, according to a Mo…
Apidog, an API development platform, published a guide explaining prompt injection as a security risk for API teams. The guide details how APIs are now called by language models and agents, making the…
Strix, an AI-powered penetration testing tool, crossed 43,400 GitHub stars and shipped v1.3.1 with GitHub Actions support, reporting only confirmed vulnerabilities with working exploits. Its multi-age…
A Go developer building a production LLM agent in a regulated field warns that the most important security rule is that the server, not the model, must determine the user's identity. The developer sho…