The story behind the intelligence

Welcome to this week’s edition of the Threat Source newsletter. Our goal is to get accurate threat intelligence to our audience as quickly as possible, with all the context you need to ask the right questions of your own environment: How at risk are we from this threat? Are we prepared for it? And what can we do about it?

Much of that abstraction is necessary. Defenders need intelligence they can use, not a complete account of every conversation we had, or investigative detour behind it. But it can create an overly tidy picture of both cybercrime and the work required to understand it.

If you do fancy a look behind the curtain, though, may I recommend our just-published episode of Beers with Talos? Our guest is Azim Khodjibaev, whose remit is adversary engagement. His work involves developing personas for deep- and dark-web research, engaging directly with threat actors, and building relationships with people who may become (and have been) openly threatening to him. At one point, he was maintaining eight separate personas, some of which were interacting with one another. Azim’s engagements have helped Talos identify prolific cybercriminals and contributed to wider disruption efforts. They have also resulted in ransomware operators placing “Azim sucks” in their code and accusing him of belonging to the very criminal groups he was investigating.

His experiences also expose the problem with treating adversaries as uniformly sophisticated operators. Some are technically capable and highly organised. Others are impulsive, ego-driven, or one-trick ponies. Many have a scary detachment from the consequences of their actions. Increasingly, Azim is seeing less-experienced threat actors working through loosely organised online collectives.

Intelligence necessarily turns that disorder into something defenders can understand and use. But occasionally, it is worth looking behind the finished product – the patience it takes to get accurate answers, who we are investigating, and the deeply human behaviour that shapes both sides.

The one big thing: Cisco Talos is highlighting a growing operational hurdle for security teams that we call the AI “safety penalty.” As frontier AI models advance, their built-in guardrails are increasingly blocking legitimate defensive tasks. This was evident in July 2026 when Hugging Face's primary cloud LLM refused to analyze forensic data during a breach, delaying their response. While defenders are slowed by these frustrating refusals, adversaries are freely leveraging unconstrained models to attack at machine speed.

Why do I care? This guardrail asymmetry hands the advantage directly to attackers. When a cloud-hosted AI model refuses a forensic request mid-incident, defenders lose precious time. Security teams are paying for vendor-imposed limitations without gaining a capability edge, especially as open-weight alternatives close the reasoning gap. Ultimately, relying on third-party alignment policies means a sudden update in Silicon Valley could quietly break your defensive workflows overnight.

So now what? Security leadership must reclaim operational sovereignty by ensuring they have the final say over their AI's capabilities. Start by auditing your AI refusal rates to measure the exact cost of this safety penalty. From there, evaluate alternative architectures like private infrastructure, Model-as-a-Service platforms, or a hybrid fallback system that reroutes refused prompts to an unconstrained local model. Read the full blog to explore these roadmaps and learn how to keep pace with adversaries.

Top security headlines of the week:

• ShinyHunters claims it stole 284 million patient records from McKesson. ShinyHunters told BleepingComputer and said it got in through vishing calls to McKesson employees, then used stolen credentials to take over Okta single sign-on accounts. (Help Net Security)
• Anthropic warns Claude users of infostealer malware infections. Anthropic emphasized that the malware is general-purpose and not tied to Claude itself, typically arriving via unofficial downloads or malicious apps. The company said the malware quietly copies saved passwords, browser login cookies, and credentials for other local applications. (Security Week)
• EU puts ChatGPT, Reddit, and Roblox under stricter DSA rules. The DSA establishes rules governing areas including platform transparency, illegal content, advertising, researcher access, recommender systems, and systemic-risk management. (CyberInsider)
• PaperCut issues emergency patches as threat actors target chained vulnerabilities. PaperCut issued the patches on Friday to address critical vulnerabilities in its print-management software. The company confirmed in a security advisory that multiple customers were successfully targeted and that it is working with security researchers to respond to the attacks. (Cybersecurity Dive)

Can’t get enough Talos? JavaScript obfuscation: From party trick to phishing kit. We've spent a lot of time pulling apart suspicious JavaScript from phishing kits, malware packages, compromised sites, and more. Learn the basics of what obfuscation is, why a researcher would try to reverse it, and several ways to approach the problem.

Choose your fighter: Balancing competing AI SOC model requirements. Selecting a model for your security operations center (SOC) and digital forensics and incident response (DFIR) tasks is important, but selecting the best one is more involved than you might think. Here's how to choose.

Beers with Talos: Eight people walk into a dark web forum. They're all Azim.