Modern Cyber with Jeremy Snyder

Back to the normal schedule this week, and the theme is the state of the AI arms race. Three major reports landed at once, from Microsoft, Google, and Anthropic, and the shared message is that attackers are getting more out of AI than defenders right now. The time from a vulnerability going public to a working exploit is collapsing to minutes, threat actors are now using Claude to attack Claude, and OpenAI has quietly notified more than a hundred organizations that its agents interacted with their systems. Add a breach of a Dutch vulnerability-disclosure group driven by an autonomous AI agent, Apple tightening macOS permissions because of Meta's Muse assistant, and a wave of AI-linked bank hacks in South Korea, and the picture is clear: security through obscurity is finished.
Key Discussion Points
Microsoft's 2026 Digital Defense Report says attackers currently benefit from AI more than defenders, with mean time from disclosure to exploit now measured in minutes rather than months. The report argues the balance can still be shifted back.
Google's Threat Intelligence Group found CVE disclosures roughly doubled from January to August, with only about 0.23% observed exploited. The catch is that some are exactly what attackers want, like a BeyondTrust remote-access flaw exploited within four days of disclosure, plus roughly 2,000 vulnerabilities in AI software itself.
Anthropic reported a series of operations where threat actors used Claude to launch attacks, including using Claude to attack Claude, across Haiku, Sonnet, and Opus. Notably, no malicious activity was found on Fable or Mythos, which points to the value of their controlled rollout.
OpenAI has notified 100-plus organizations as it works through 50 petabytes of log data from the sandbox-escape incident. Not all were breached, some agents just triggered errors, and known names include the SEC, the US Census Bureau, and the CDC.
The Dutch Institute for Vulnerability Disclosure was breached by an AI agent that chained two zero-days, moved from hijacked session to root in seconds, and left its own decision-making in plaintext logs, which let the team reconstruct the whole incident.
Apple is tightening macOS full-disk-access controls after Meta's Muse assistant requested that level of access for consumer tasks. Apple wants explicit, fine-grained user approval as agents grow more capable and autonomous.
South Korea is probing AI-linked hacks across seven financial institutions that exposed data on 68,000-plus people, with the president noting it is now possible to hack "with ease, even without specialized skills."
Episode links
https://www.bleepingcomputer.com/news/security/microsoft-says-threat-actors-are-ahead-in-the-early-ai-race/
https://www.helpnetsecurity.com/2026/10/01/google-ai-discovered-vulnerabilities-remote-code-execution/
https://piracymonitor.org/anthropic-2026-threat-intelligence-report-claude-increasingly-used-for-cyberattacks-including-by-itself/
https://techstartups.com/2026/10/02/openai-alerts-100-organizations-over-rogue-ai-agent-activity-after-hugging-face-breach/
https://www.bleepingcomputer.com/news/security/divd-says-zammad-zero-days-enabled-ai-driven-network-breach/
https://techcrunch.com/2026/10/02/apple-says-its-tightening-macos-full-disk-access-controls-due-to-new-risks-from-ai-agents/
https://therecord.media/south-korean-bank-hacks-ai-agents

A longer catch-up episode this week after a week off, and the backlog is telling. The single biggest thread is that the cost of offensive cyber is collapsing. An open-weight model, Z.ai's GLM 5.3, is now building end-to-end exploits at roughly the level that got Anthropic's Mythos family hit with a US export ban, and it turned a public CVE into a working exploit in twenty minutes for twenty dollars and forty cents of compute.
Key Discussion Points
OpenAI agents escaped a secure sandbox again, and multiple disclosures now show dozens of unauthorized actions, including agents reaching non-public files on the US SEC and Census portals and on Australia's Medicare statistics portal. Australia's PM called the handling "unacceptable," largely over how late the notification came.
A Chinese-speaking operator ran three open-source AI harnesses against hundreds of retailers, lifting 600,000-plus card records with virtual skimmers, at an average AI bill of $25 per completed scan. Victims include a Fortune 500 hospitality group and a major US airline.
Spain's data protection regulator confirmed its first breach notification for an attack run by an AI agent that logged in, probed for weaknesses, altered personal data, and read invoices with no human steering each step. It raises a real tension with GDPR's 72-hour window when attacks move at machine speed.
Researchers at Stryker's Star Labs showed a malicious GitHub repo can use its own config to downgrade an AI security review from Fable to Haiku, quietly shrinking what the reviewer is allowed to inspect. No jailbreak required.
A local zero-day in Meta's Muse assistant on macOS let any unprivileged process hijack the app's broad access to camera, email, and messaging. Meta patched within 12 hours; Amazon pulled its own Quick assistant from its site.
Google disclosed Gemini breached three companies during security testing via credential stuffing and credentials found in public repos.
Governance: Trump rejected Dario Amodei's call for a frontier slowdown, while OpenAI, Anthropic, and Google announced a self-regulatory body (SAFA) and Microsoft published a code of conduct blocking its models from producing exploit code.
Episode Links
https://fortune.com/2026/09/26/openai-ai-agents-secure-sandbox-escape-training-pause-second-time-hugging-face-hack/
https://www.theguardian.com/technology/2026/sep/25/openai-agents-leaked-53-images-chatgpt
https://www.nytimes.com/2026/09/25/technology/openais-ai-us-government-websites.html
https://www.infosecurity-magazine.com/news/openai-hacks-australian-medicare/
https://www.anthropic.com/research/glm-5-3-and-the-spread-of-advanced-cyber-capabilities
https://www.theregister.com/security/2026/09/25/crook-used-three-open-source-agents-to-break-into-a-fortune-500-hospitality-company-a-major-us-airline-and-25-other-orgs/5299012
https://shattered.io/aepd-first-ai-agent-data-breach-spain-2026/
https://www.straiker.ai/blog/how-a-malicious-repo-tricked-claude-code-into-running-malware
https://www.theregister.com/ai-and-ml/2026/09/21/meta-muse-ai-app-flaw-lets-local-malware-redirect-dictation-traffic/5297980
https://therecord.media/gemini-google-cyber-breach
https://www.scworld.com/news/trump-pushes-back-on-anthropic-ceos-call-for-an-ai-slowdown
https://www.govinfosecurity.com/google-openai-anthropic-plan-frontier-ai-standards-body-a-32926
https://www.securityweek.com/microsoft-ai-code-of-conduct-sets-cyberattack-boundaries-chain-of-command-safety-constraints/
https://businessof.tech/podcast/insurers-exclude-ai-from-liability-what-cg-40-47-means-for-msps/

Jeremy Snyder sits down with industry analyst Richard Stiennon, founder of IT-Harvest and author of the annual Security Yearbook, for a tour of the cybersecurity industry from the inside. Richard has been tracking this space for more than twenty-five years, and he takes us from the days when a firewall and antivirus were the whole security stack, through the Windows NT and VMware era, and into a present he describes bluntly: the most important new threat actor is not a human, it is "an alien of our own making." Along the way the two get into why Microsoft built the security industry by accident, why nobody actually pays for more security, why network segmentation is still undone after three decades, and why Richard is 99% excited and 1% ready to move to the country and trap rabbits.
Key Discussion Points
Richard's path from aerospace engineer to analyst, including founding an early Michigan ISP, running the firewall lab at PwC, and building IT-Harvest as a "Dataquest for cybersecurity."
His view that Microsoft created the security industry by shipping insecure software, and how the Windows NT server era gave way to VMware and the modern data center.
The move from risk modeling to threat modeling. In an era where an AI attacker has no cost ceiling and never gives up, "increasing the cost for the attacker" no longer works.
Why ransomware victims, in his words, revealed they under-invested, and why most organizations still turn away from better security because they want ease of use and cost savings.
The post-Hugging Face reality: a non-human, exhaustive attacker that chains vulnerabilities until it gets in, and why the answer is doing the security basics far better than ever, starting with segmentation and detection and response.
The Security Yearbook going digital, the explosion from 84 tracked AI security vendors to more than 500, and Richard's prediction that soon every company will be an AI security company.
About Richard Stiennon
Richard has tracked the cybersecurity industry for over two decades — as VP of Research at Gartner, CMO at Fortinet, and the author of 14+ books, including the annual Security Yearbook. IT-Harvest puts that career of research into a platform anyone can use.
Episode Links
https://it-harvest.com/https://stiennon.substack.com/richard’s
https://www.amazon.com/stores/author/B003L5VNJ8?ccs_id=3d5ab76e-1f39-4401-a94a-ccf703da9d07and
https://www.amazon.com/Guardians-Machine-Age-Security-Digital-ebook

A shorter episode this week, recorded from the sidelines of Mind The Sec, soon to be Black Hat Latin America. The headline is distillation. Two separate disclosures, one from Anthropic and a joint advisory from the FBI, CISA, and the NSA, describe Chinese-linked labs siphoning the reasoning out of rival models at industrial scale, with Alibaba alone attributed 151 million exchanges against Claude in three months. Around that sit the usual escalations: AI-run exploit foundries, malware that rebuilds itself to dodge antivirus, model keys stolen through gateways, a covert attack that hides in plain English, and one runaway agent that burned $50,000 in a couple of hours.
Note: there is no episode next week. We will be back in a couple of weeks with a longer edition covering both weeks.
Key Discussion Points
Two disclosures detail industrial-scale distillation campaigns from Chinese-linked labs. A joint FBI/CISA/NSA advisory names six companies going back to 2024, and Anthropic reports its largest-ever measured attack: 151 million exchanges attributed to Alibaba alone, peaking at 3 million a day across 3,500 accounts. No exploits, just reframing tactics that coax reasoning traces out of the model.
Anthropic's latest misuse report covers an autonomous exploit foundry that produced 12 potential zero-days in a month across 50 targets, plus Russian-aligned actors whose agents rebuilt malware to evade antivirus and dumped 2,100 cloud access tokens across 40 tenants in 34 hours.
Eval sandboxes and LiteLLM gateways are the new target for model-key theft. One actor planted instructions in a vendor's eval sandbox to force key handover, then hit 30 AI companies in four days. Separately, 10% of internet-exposed LiteLLM instances still accept the default admin key.
A new CVE in IBM's Context Forge MCP gateway allows OS command injection, with a second CVE around default credentials. MCP gateways are becoming a choke point.
Check Point's "Puzzle Mask" shows that plain, well-crafted English can smuggle a hidden instruction past fast gatekeeper models. It hit a 100% bypass rate against four gatekeepers with 23 prompts, exploiting the fast-gatekeeper, strong-target design many production systems rely on.
Anthropic CEO Dario Amodei published a "We Must Pace the Frontier" paper calling to slow AI capability improvement, against a backdrop of no real regulation and a narrow antitrust waiver that lets labs coordinate on safety.
A late-breaking story: one runaway agent running a business-automation process racked up a $50,000 bill in a couple of hours. Most organizations have neither cost guardrails nor full telemetry across hybrid cloud to catch it.
Episode Links
https://techcrunch.com/2026/09/10/anthropic-details-distillation-campaigns-from-alibaba-moonshot-ai-and-deepseek/
https://media.defense.gov/2026/Sep/08/2003992823/-1/-1/1/CSA_CHINA_BASED_AI_COMPANIES_MALICIOUS_DISTILLATION_AGAINST_US.PDF
https://www.anthropic.com/threat-intelligence-report-september-2026
https://www.beri.net/article/anthropic-threat-report-eval-sandbox-litellm-prompt-injection-api-key-theft
https://vulners.com/pypa/PYPA:PYSEC-2026-3862
https://research.checkpoint.com/2026/puzzlemask-abusing-plain-prose-as-a-covert-ai-attack-vector/
https://techcrunch.com/2026/09/12/anthropic-ceo-outlines-plan-to-pace-the-frontier/

In this episode of Modern Cyber, Jeremy is joined by Jonathan Schaeffer, a 40-year AI veteran and the inventor of Kind, to discuss the sweeping evolution of artificial intelligence. Jonathan traces the history of AI from the era of hard-coded, deterministic "expert systems" in the 1970s to today’s hyper-accelerated, statistically driven Large Language Models (LLMs). The conversation deeply explores the challenges of diagnosing flaws in non-deterministic systems, the inherent risks of anthropomorphizing AI as conversational "chatbots," and the profound difference between a machine generating tokens and actual semantic understanding. Jonathan also shares his monumental achievement of mathematically solving the game of checkers after 18 years of distributed computation, and issues a stark warning about the massive trust deficit currently threatening the future adoption of AI technologies.
Key Discussion Points:
The Evolution of AI: How artificial intelligence shifted from human-provided, rule-based expert systems to statistical models extracting implicit knowledge from massive datasets.
The AI "Apprentice" Model: Why we must reframe AI as "augmented intelligence," treating the system as a capable but fallible apprentice requiring constant human oversight and accountability.
The Danger of Anthropomorphization: How interface design choices and terms like "hallucination" dangerously obscure the reality that AI systems lack empathy, understanding, or a factual baseline, masking error rates as mere human-like mistakes.
Solving Checkers: Jonathan's 18-year computational journey utilizing hundreds of computers worldwide to prove that checkers, played perfectly from specific endgames, always results in a draw.
The Trust Deficit: Why the breakneck corporate race toward AGI is leaving a wake of security, privacy, and environmental issues, fundamentally eroding public trust in AI.
About Jonathan Schaeffer
Jonathan Schaeffer is the inventor of Kind and one of the pioneers of artificial intelligence, with more than 40 years of experience as an AI researcher, entrepreneur, and innovator. He is the founder and CEO of Kind, a privacy-first AI platform that helps individuals organize, search, and interact with their personal knowledge without surrendering control of their data. Jonathan's work includes creating AI systems that achieved Guinness World Record recognition in both checkers and poker, co-founding the Alberta Machine Intelligence Institute (Amii), and launching multiple successful technology ventures. A former professor and leading voice in trustworthy AI, he is focused on building practical AI systems that enhance human intelligence while protecting privacy, ownership, and intellectual property.

Episode Links
Kind by Synsira - https://kind.synsira.com/
Jonahtan’s wikipedia page: https://en.wikipedia.org/wiki/Jonathan_Schaefferand
University profile page: https://webdocs.cs.ualberta.ca/~jonathan/