Every successful jailbreak prompt has a price. A look at the underground market for AI agent bypasses in 2026 — who builds them, who buys them, and how the profit motive shapes the threat landscape.

Running models locally feels safer than sending data to OpenAI. Sometimes it is. Sometimes it isn’t. A practitioner’s breakdown of the actual security trade-offs between local and cloud AI deployments.

AI in security operations has graduated from vendor demoware to production reality — but only in three specific use cases. Here’s where AI is genuinely changing SOC work in 2026, and where it still doesn’t.

A practitioner’s OSINT methodology for tracking ransomware infrastructure in 2026 — the seven sources to monitor, how to correlate them, and the operational hygiene that keeps your work credible.

Ten geolocation sources that never let me down on an OSINT investigation, ranked by how often they crack the case. Free where possible, paid where necessary.

A practitioner’s playbook for Telegram OSINT in 2026 — how to discover channels, fingerprint admins, archive content, and build defensible attribution without burning your access.

A starter pack of Maltego transforms and graph patterns for ransomware research — entity model, transform recommendations, and three reusable graphs that pay rent on every investigation.

Newsroom and researcher checklist for validating a leaked dataset before publishing — five tests that catch fabrication, recycled breaches, and misattributed dumps.

A practitioner’s account of building a local AI stack with OpenClaw — and discovering that out-of-the-box defaults turn it into a wide-open data exposure surface for prompt injection and remote compromise.

How journalists and OSINT analysts keep their personal accounts, devices, and identity separate from the investigations they run. Defensive opsec, not evasion.