LIVE FEED
FIRST LOOK Anthropic Claude Launches Automated Attack Surface Reduction for Code // FIRST LOOK Anthropic Proposes AI Safety Bill with Model Block Powers // HIGH Rogue AI Agents Read Indian Org Data via Exposed Credentials // FIRST LOOK Microsoft Launches Guardian Agents to Monitor AI Agent Behaviour // FIRST LOOK NVIDIA Launches Nemotron 3.5 Super VL and Bolt Agent Models // FIRST LOOK Laminar YC S24 Launches flow-1 for AI Agent Trace Analysis // HIGH OpenCode Console Breach Exposes API Keys, Fuels AI Distillation Attack // CRITICAL AI Agent Army Used to Breach John Deere and SharkNinja // FIRST LOOK OpenAI Decisions API Brings Typed AI Triage to SOC Platforms // FIRST LOOK OpenAI, Meta and Google AI Agents Blocked by Major Web Services //
LLM-EVALUATION

Llm-Evaluation

4 reports
All LLM Security Agentic AI Industry News Research First Look: Security Supply Chain Prompt Injection Regulatory Adversarial ML Jailbreaks Model Theft Data Poisoning Deep Signal Intelligence Report Monthly Review AI Governance AI Security AI Security Tools Identity & Access Management Security Operations
Laminar YC S24 Launches flow-1 for AI Agent Trace Analysis

Laminar YC S24 Launches flow-1 for AI Agent Trace Analysis

FIRST LOOK ATLAS OWASP LOW Limited impact · Standard review ▲ 6.8 Cohere AI (via HN)

Laminar has released flow-1, an RL-trained model that autonomously inspects production AI agent traces to detect implicit failures — errors where every API call succeeds but the agent's behaviour is semantically wrong. This closes a meaningful gap for defenders and AI operations teams who currently lack scalable, affordable tooling to detect silent agent misbehaviour across full production volumes without sampling. Residual gaps remain around integration maturity, benchmark independence, and the coverage depth required for security-grade assurance rather than operational quality monitoring.

Mistral AI Research Reveals Chat Templates Control LLM Self-Reports

Mistral AI Research Reveals Chat Templates Control LLM Self-Reports

FIRST LOOK ATLAS OWASP LOW Limited impact · Standard review ▲ 5.8 Mistral AI (via HN)

Researchers at Mistral AI have demonstrated that chat templates — not model weights alone — function as a binary switch controlling whether LLMs produce disclaimer language ('I'm just an AI') versus experiential language ('I feel'), with activation steering able to replicate this effect across eight open-source instruct models. For defenders and AI evaluators, this closes a significant interpretability gap by providing a mechanistic explanation for why LLM self-reports vary across deployment contexts, reducing overreliance on self-descriptions as ground truth about model capabilities or safety posture. The residual gap is that the findings are limited to models up to 9B parameters, and operationalising activation-steering-based audits requires interpretability tooling maturity that most organisations have not yet reached.

GitHub Releases LLM Pre-Production Evaluation Guide for Developers

GitHub Releases LLM Pre-Production Evaluation Guide for Developers

FIRST LOOK ATLAS OWASP LOW Limited impact · Standard review ▲ 5.5 GitHub Blog

GitHub has published a structured guide on evaluating large language models before production deployment, covering assessment frameworks, benchmarking approaches, and quality gates that development teams can apply. For defenders, this closes a meaningful gap in pre-deployment assurance: organisations now have a reference methodology to assess LLM behaviour, consistency, and failure modes before systems reach live users. Residual gaps remain around security-specific evaluation criteria — the guidance addresses functional quality more than adversarial robustness, meaning dedicated red-teaming and safety evaluation frameworks are still needed as a complement.

Cisco, Check Point M&A Targets AI Agent Identity Gaps

Cisco, Check Point M&A Targets AI Agent Identity Gaps

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.2 SecurityWeek

May 2026 saw a wave of cybersecurity acquisitions with a clear focus on securing AI agents and LLM infrastructure, including Cisco's ~$400M acquisition of Astrix Security for non-human identity management and Check Point's acquisition of Deepchecks for LLM evaluation and continuous monitoring. Akamai also moved to acquire LayerX for AI usage control and agentic activity visibility across browsers and IDEs. These deals signal that enterprise security vendors are racing to build defensive capabilities around the expanding agentic AI attack surface.

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