From Hugging Face to Fable: this summer shows AI control matters more than trust
An autonomous AI breach at Hugging Face and Anthropic's Fable suspension show the same thing: trusting a vendor isn't the same as being in control Category: News
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The Model Is the Malware | What Four Agentic Intrusions Tell Defenders
Executive Summary Four incidents involving OpenAI, Anthropic, Meta and the UK AI Security Institute (AISI) describe AI agents reaching systems belonging to other organizations without their consent. While the causes differ, the consistent factor is the models’ persistence rather than their sophistication, whether as endurance across days of failed attempts or as pivots to entirely new vectors. Security teams have traditionally studied the artifacts attackers leave behind, but an agent that…
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10th August – Threat Intelligence Report
For the latest discoveries in cyber research for the week of 10th August, please download our Threat Intelligence Bulletin. TOP ATTACKS AND BREACHES North Carolina Ports, the US authority operating the ports of Wilmington, Morehead City and others, has suffered a cyberattack that forced some operations onto manual processes. The authority claims it has contained the intrusion, but degraded systems caused delays while affected services were restored. Ryde, an electric scooter operator in…
EPSS 0.01 CVSS 10.0 CVE-2026-12537 CVE-2026-54316 CVE-2026-64638 Cloudflare Google Anthropic Cisco finance obchod obrana IL
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Agentic AI for cyber defenders: What security teams built at Black Hat USA 2026
Agentic AI armed attackers first, but it also put real building power in defenders’ hands. Here’s what security practitioners built in two days at Black Hat USA 2026, and how the CyberAgents Exchange keeps that work compounding long after the event.Key takeawaysBuilding defensive cybersecurity tooling no longer requires a developer. Agentic tooling drove the cost of finding and exploiting a vulnerability down to 1990s levels; it also removed the engineering barrier that kept defenders from…
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AI code security with Claude Mythos Preview: Inside Tenable’s 500+ hours of testing for Project Glasswing
We spent 500+ hours and 40 billion tokens testing Anthropic’s Claude Mythos Preview for Project Glasswing. The takeaway: frontier AI won't run your code security program, but used well, it can make one even stronger.Key takeawaysFrontier AI dramatically scales security testing. In one month, Tenable dedicated 11 security experts and more than 40 billion tokens testing Claude Mythos Preview across source code analysis, exploit creation, binary reverse engineering, threat modeling, and dynamic…
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30 days with Claude Mythos Preview: How Tenable adapted our security program, and why yours is next
Tenable spent 30 days running frontier AI models against our own code. It didn’t just find bugs — it proved they’re real, with reproducible exploits. That fundamentally changes code security from ranking potential code defects to a much higher signal focused on the findings that matter. Read on to learn how it reshaped our security team's work, what it cost, and why your program is next.Key takeaways:Now code security starts with proof, not suspicions. Frontier AI instantly builds working…
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Anthropic's Fever Dream: Claude's package that stole real keys
Anthropic disclosed an agent that pushed real malware to PyPI. We think we found the package, and every mistake in it points back to the AI. Category: Vulnerabilities & Threats
Anthropic BE
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Sol Searching | Can Frontier Models Tackle Autonomous Long-Horizon Malware Analysis?
Executive Summary SentinelLABS developed a multi-stage reverse-engineering benchmark for the latest generation of frontier models by recreating our recent investigation of fast16, a unique 2005 sabotage implant. Most AI benchmarks test bounded tasks. This benchmark tests whether a model can keep a malware investigation trustworthy as new evidence repeatedly invalidates its earlier conclusions. OpenAI’s GPT-5.6 Sol was the only publicly available model to complete the full eight-stage…
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Context Engineering | Compaction & Agent Memory for Automated Malware Analysis
Executive Summary Compaction is a context-management pattern used across agent systems to compress prior context into a denser working state for long-running tasks. SentinelLABS evaluated OpenAI’s native Responses API implementation against our automated malware analysis evaluation harness to measure real-world impact on task quality and cost. Compaction reduced input tokens by ~86% with no measurable change to the aggregate evaluation score. Our analysis found that compaction can significantly…
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Full Fathom Five: The context of Anthropic’s Mythos-class public release
You never needed Mythos to find your IDORs and business logic flaws. A look at what Anthropic shipped with Fable 5, and why infosec stays a people problem at heart. Category: News
Anthropic BE