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As large language models become more capable, users are tempted to delegate knowledge tasks where models process documents on their behalf and provide the finished results. But how far can you trust the model to stay faithful to the content of your documents when it has to iterate over them across multiple rounds? A new…

Any development environment that installed or imported one of the 172 compromised npm or PyPI packages published since May 11 should be treated as potentially compromised. On affected developer workstations, the worm harvests credentials from over 100 file paths: AWS keys, SSH private keys, npm tokens, GitHub PATs, HashiCorp Vault tokens, Kubernetes service accounts, Docker…

AI that can see and understand what’s happening in a video — especially a live feed — is understandably an attractive product to lots of enterprises and organizations. Beyond acting as a security “watchdog” over sites and facilities, such an AI model could also be used to clip out the most exciting parts of marketing…

Between May 6 and 7, four security research teams published findings about Anthropic’s Claude that most outlets covered as three separate stories. One involved a water utility in Mexico, another targeted a Chrome extension, and a third hijacked OAuth tokens through Claude Code. In one case, Claude identified a water utility’s SCADA gateway without being…

Presented by Apptio, an IBM company AI spending is surging, but the full impact often remains an open question. Closing the gap requires clear answers to how AI is governed, measured, and tied to business outcomes. ROI uncertainty isn’t unique to AI: In the Apptio 2026 Technology Investment Management Report, 90% of technology leaders surveyed…

Presented by EdgeVerve For most enterprises, AI adoption began with a straightforward ambition: automate work faster, cheaper, and at scale. Chatbots replaced basic service requests, machine‑learning models optimized forecasts, and analytics dashboards promised sharper insights. Yet many organizations are now discovering that deploying individual AI solutions does not automatically translate into enterprise‑level impact. Pilots proliferate,…

Is AI leaving the era of “turn-based” chat? Right now, all of us who use AI models regularly for work or in our personal lives know that the basic interaction mode across text, imagery, audio, and video remains the same: the human user provides an input, waits anywhere between milliseconds to minutes (or in some…

A doctor in a hospital exam room watches as a medical transcription agent updates electronic health records, prompts prescription options, and surfaces patient history in real time. A computer vision agent on a manufacturing line is running quality control at speeds no human inspector can match. Both generate non-human identities that most enterprises cannot inventory,…

AI agents choose tools from shared registries by matching natural-language descriptions. But no human is verifying whether those descriptions are true. I discovered this gap when I filed Issue #141 in the CoSAI secure-ai-tooling repository. I assumed it would be treated as a single risk entry. The repository maintainer saw it differently and split my…

Here is a scenario that should concern every enterprise architect shipping autonomous AI systems right now: An observability agent is running in production. Its job is to detect infrastructure anomalies and trigger the appropriate response. Late one night, it flags an elevated anomaly score across a production cluster, 0.87, above its defined threshold of 0.75. The…