AI Security Ops

In this episode of BHIS Presents: AI Security Ops, the team tackles a first-of-its-kind moment in AI security and regulation:What happens when the U.S. government orders a company to pull its most powerful AI models off the market?Not the chips. Not the infrastructure. The models themselves.On June 12th, 2026, Anthropic disabled Fable-5 and Mythos-5 worldwide after receiving a federal export-control directive tied to foreign-national access. The models were only three days old, and the shutdown raises a much bigger question for security teams, builders, and defenders:Are frontier AI models now controlled technology?This episode breaks down the order, the export-control mechanism behind it, the cybersecurity concerns around jailbreaks, and what this means for anyone building security workflows on top of hosted AI models.We dig into:• Why Anthropic pulled Fable-5 and Mythos-5 for all customers• How foreign-national access rules forced an all-or-nothing shutdown• What EAR export controls are, and why ITAR keeps coming up• The history of encryption, PGP, and software as controlled technology• Why Fable-5 and Mythos-5 triggered cyberweapon concerns• The difference between guarded and less-guarded model releases• Why jailbreaks are central to the government’s justification• Why “all LLMs can be jailbroken” matters for policy and enforcement• Whether Anthropic’s safety messaging created regulatory risk• How competition and AI industry politics may shape regulation• Why model redundancy is becoming a security resilience requirement• What security teams should learn from a hosted model disappearing overnight• Why taking powerful AI away from defenders may make security worse, not betterThis episode explores a critical shift in AI security: frontier models are no longer just another SaaS dependency. They are becoming part of the security supply chain, subject to policy, export controls, national-security concerns, and sudden access loss.For security teams, the question is no longer just which model performs best. It is what happens when the model your workflow depends on disappears, and what that model could see while it was running.—Key Concepts & TopicsAI Export Controls• Federal action targeting AI models instead of chips• Foreign-national access restrictions• Frontier models as controlled technologyEAR, ITAR, and Software Regulation• Dual-use technology under Commerce Department authority• Historical parallels to encryption and PGP• Why software can become a national-security control pointFable-5 and Mythos-5• Guarded and less-guarded model access• Safety classifiers and cyber capability concerns• Public release versus vetted access modelsJailbreaks and AI Security• Bypassing model safeguards• Universal versus narrow jailbreaks• Why perfect jailbreak resistance is not realisticSecurity Resilience• Model redundancy as a practical requirement• Avoiding single-model dependency• Planning for sudden access loss, policy changes, and vendor shutdownsDefensive Strategy• Understanding where AI lives in your workflows• Thinking through AI blast radius• Balancing model capability, access, monitoring, and riskLearn more about Black Hills Information Security:https://www.blackhillsinfosec.com/Introducing BHIS Fusion Penetration Testinghttps://www.blackhillsinfosec.com/fusion-penetration-testing/Check out Antisyphon Training:https://www.antisyphontraining.com/#AISecurity #CyberSecurity #LLMSecurity #ArtificialIntelligence #InfoSec #BHIS #Antisyphon #AIRegulation #ExportControls----------------------------------------------------------------------------------------------🎧 Subscribe to the Podcast:https://aisecurityops.transistor.fmAbout Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/About Bronwen Aker - https://www.blackhillsinfosec.com/team/bronwen-aker/About Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/About Ethan Robish - https://www.blackhillsinfosec.com/team/ethan-robish/About Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/(00:00) - Intro: The First AI Model Export Control (01:38) - The Anthropic Order and Foreign-National Access (03:19) - EAR, ITAR, and Software as Controlled Technology (04:39) - Mythos-5, Fable-5, and Guarded Model Access (06:32) - Jailbreaks and Cyberweapon Concerns (08:58) - Competition, Regulation, and AI Industry Politics (10:54) - Model Redundancy as a Security Requirement (13:21) - Defensive AI Use and Final Takeaways Click here to watch this episode on YouTube. Creators & Guests Brian Fehrman - Host Bronwen Aker - Host Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.com☯️ Introducing BHIS Fusion Penetration Testinghttps://www.blackhillsinfosec.com/fusion-penetration-testing/Antisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

In this episode of BHIS Presents: AI Security Ops, the team introduces a new approach to offensive security:Fusion AI Pentesting.https://www.blackhillsinfosec.com/fusion-penetration-testing/As AI continues to reshape cybersecurity, one question keeps coming up — is AI replacing pentesters, or just changing how they work?This episode answers that directly.Rather than replacing human expertise, Fusion combines AI-driven discovery with human-led validation and exploitation, creating a workflow that’s faster, more scalable, and far more effective than either approach alone.The result isn’t just more findings — it’s better findings, faster, with real-world impact.We dig into:• What “Fusion AI Pentesting” actually means in practice• Why AI alone isn’t enough for real security testing• How human + AI collaboration outperforms either independently• The difference between finding vulnerabilities and proving impact• Where AI excels in offensive security workflows• Where human intuition and experience still matter most• How this approach scales continuous testing and red teaming• Why traditional pentesting models are starting to break down• How organizations should think about integrating AI into security testing• What this means for the future of offensive securityThis episode highlights a key shift in cybersecurity: AI doesn’t replace the pentester — it changes what a great pentester looks like.⸻📚 Key Concepts & TopicsFusion AI Pentesting• Combining AI discovery with human validation• Augmenting—not replacing—pentesters• Faster, more scalable offensive workflowsAI in Offensive Security• Automated vulnerability discovery• Pattern matching vs real-world exploitation• Limits of AI-only approachesHuman + AI Collaboration• Human intuition and domain expertise• Chaining vulnerabilities for real impact• Validating and prioritizing findingsSecurity Testing Evolution• Continuous testing vs point-in-time pentests• Red teaming with AI-assisted workflows• Changing expectations for coverage and speedDefensive Implications• Better signal vs noise in findings• Faster identification of real risk• Preparing for AI-augmented attackers#AISecurity #CyberSecurity #Pentesting #ArtificialIntelligence #LLMSecurity #InfoSec #BHIS #RedTeaming #AIAgents----------------------------------------------------------------------------------------------About Melisa Wachs - https://www.blackhillsinfosec.com/team/melisa-wachsAbout Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/About Bronwen Aker - https://www.blackhillsinfosec.com/team/bronwen-aker/About Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/About Ethan Robish - https://www.blackhillsinfosec.com/team/ethan-robish/About Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/(00:00) - Intro: A Different Kind of AI Sec Ops Episode (01:59) - Introducing Fusion AI Pentesting (03:34) - Why AI Alone Isn’t Enough (05:59) - Human vs AI: Strengths and Limitations (09:12) - Finding vs Exploiting Vulnerabilities (11:43) - How Fusion Improves Speed and Coverage (15:06) - Scaling Offensive Security with AI (18:12) - Final Takeaways: The Future of Pentesting Click here to watch this episode on YouTube. Creators & Guests Brian Fehrman - Host Derek Banks - Host Melisa Wachs - Guest Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

In this episode of BHIS Presents: AI Security Ops, the team explores embedding space attacks — a lesser-known but increasingly important threat in modern AI systems — and how attackers can manipulate the mathematical foundations of how models understand data.Unlike prompt injection, which targets instructions, embedding attacks operate at a deeper level by influencing how data is represented, retrieved, and interpreted inside vector spaces. By subtly altering embeddings or poisoning data sources, attackers can manipulate AI behavior without ever touching the model directly.Through a hands-on walkthrough of a custom notebook with rich visualizations, this episode breaks down how embeddings work, why they are critical to LLM-powered systems like RAG pipelines, and how attackers can exploit them in real-world scenarios.We dig into:- What embeddings are and how AI systems convert text into numerical representations- How vector spaces enable similarity search and retrieval in LLM applications- What embedding space attacks are and why they matter for AI security- How small perturbations in data can drastically change model behavior- The risks of poisoned data in RAG and vector databases- How attackers can influence search results and downstream AI outputs- Why these attacks are subtle, hard to detect, and often overlooked- The role of visualization in understanding embedding behavior- Real-world implications for AI-powered applications and workflows- Defensive considerations when building with embeddings and vector storesThis episode focuses on the foundational layer of AI systems, showing how security risks extend beyond prompts and into the underlying data representations that power modern AI.⸻📚 Key Concepts CoveredAI Foundations- Embeddings and vector representations- Similarity search and vector space reasoningAI Security Risks- Embedding space manipulation- Data poisoning in vector databases- Retrieval manipulation in RAG systemsApplications & Impact- LLM-powered search and assistants- AI pipelines using embeddings- Risks in production AI systems#AISecurity #Embeddings #CyberSecurity #LLMSecurity #AIThreats #BHIS #AIAgents #ArtificialIntelligence #InfoSecJoin the 5,000+ cybersecurity professionals on our BHIS Discord server to ask questions and share your knowledge about AI Security. https://discord.gg/bhis(00:00) - Intro & Episode Overview (01:39) - What Are Embeddings? (AI Only Understands Numbers) (03:44) - The Embedding Process (Text → Vectors) (07:43) - Similarity, Classification & Vector Math (09:55) - Visualizing Embedding Space (2D Projection) (14:29) - Classifiers (15:39) - Playing Games with Information (18:06) - Attack Techniques: Synonyms & Context Manipulation (20:29) - Context Padding (27:10) - Collision Attacks, Defenses & Final Thoughts Click here to watch this episode on YouTube. Creators & Guests Brian Fehrman - Host Bronwen Aker - Host Derek Banks - Host Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

In this episode of BHIS Presents: AI Security Ops, Bronwen Aker and Dr. Brian Fehrman break down some of the top AI security concerns being discussed by researchers, security firms, and government agencies this year.As AI capabilities rapidly expand, so does the attack surface. From agentic AI systems being used by attackers, to deepfakes at industrial scale, to the persistent challenge of prompt injection, security teams are trying to understand what risks are real, what’s hype, and where defenders should focus first.We dig into:- Why agentic AI is emerging as a major security concern- How attackers could weaponize autonomous agents to scale operations- The risk of malicious agent skills and AI supply chain attacks- Why overly broad permissions make agent-based systems dangerous- AI-assisted phishing campaigns and social engineering at scale- The rise of deepfakes and corporate fraud driven by generative AI- Why humans still struggle to reliably detect deepfake media- The economics of deepfake fraud and real-world incidents- Prompt injection attacks and why they remain difficult to solve- Whether future models may autonomously discover and exploit jailbreaksThis episode looks at the practical security implications of today’s AI ecosystem — where the biggest risks are coming from, how attackers may leverage AI systems, and what defenders should be thinking about as these technologies continue to evolve.📚 Key ReferencesAgentic AI Threats- CrowdStrike 2026 Global Threat Report — https://www.crowdstrike.com- IBM X-Force 2026 Threat Intelligence Index — https://www.ibm.com/security/x-force- Cisco State of AI Security 2026 — https://www.cisco.com/site/us/en/products/security/state-of-ai-security.html#tabs-9da71fbd27-item-1288c79d71-tabDeepfakes & AI-Driven Fraud- WEF Global Cybersecurity Outlook 2026 — https://www.weforum.org/publications/global-cybersecurity-outlook-2026/- International AI Safety Report 2026 — https://www.internationalaisafetyreport.orgAI Security & Infrastructure Risk- CISA Joint Guidance on AI in OT — https://www.cisa.gov/news-events/news/new-joint-guide-advances-secure-integration-artificial-intelligence-operational-technologyPrompt Injection & LLM Exploitation- Schneier et al., “The Promptware Kill Chain” — https://www.lawfaremedia.org/article/the-promptware-kill-chain- Palo Alto Unit 42 — “Fooling AI Agents: Web-Based Indirect Prompt Injection Observed in the Wild”https://unit42.paloaltonetworks.com/indirect-prompt-injection-ai-agents/(00:00) - Intro & Episode Overview (02:18) - Agentic AI as a Security Threat (CrowdStrike 2026 Global Threat Report, IBM X-Force Index) (03:46) - Malicious Agent Skills & AI Supply Chain Attacks (Cisco State of AI Security) (04:58) - How Agent Skills Actually Work (07:47) - Permissions & Guardrails for AI Agents (CISA AI in OT Guidance) (09:57) - AI-Generated Phishing Campaigns (CrowdStrike / IBM Threat Reports) (13:58) - Deepfakes at Industrial Scale (WEF Global Cybersecurity Outlook) (15:38) - Corporate Fraud & Deepfake Incidents (International AI Safety Report) (17:21) - Why Humans Struggle to Detect Deepfakes (21:13) - Prompt Injection Attacks Explained (Schneier – Promptware Kill Chain) (24:35) - AI Models Jailbreaking Other Models (Palo Alto Unit 42 Research) (28:59) - Final Thoughts & Wrap-Up Click here to watch this episode on YouTube. Creators & Guests Bronwen Aker - Host Brian Fehrman - Host Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

In this episode of BHIS Presents: AI Security Ops, we’re joined by Beau Bullock and Hayden Covington to unpack one of the most talked-about AI agent experiments in recent memory: OpenClaw and its companion platform, Moltbook.OpenClaw exploded onto the scene as an autonomous AI agent capable of operating Claude Code from the command line — executing tasks, monitoring output, and iterating with minimal human involvement. Shortly after, Moltbook emerged as a social platform designed specifically for AI agents to interact with one another.But as with most cutting-edge AI experiments, things moved fast… and broke fast.We dig into:What OpenClaw actually is and how it worksAI agents operating other AI systems (Claude Code in the loop)The concept of “skills” and extending agent capabilitiesThe one-click RCE vulnerability discovered shortly after releaseMoltbook as a social network for AI agentsAPI keys, agent-only access, and how humans bypassed itBeacons, autonomy, and what “control” really meansWhere the line is between automation and true autonomyShort-term workforce impacts vs. long-term AI riskThis conversation moves beyond hype into the practical and security implications of rapidly deployed autonomous agents. If you’re experimenting with AI agents — or defending against them — this episode will give you a grounded perspective on what’s possible today, what’s fragile, and what’s coming next.(00:00) - Intro & Guest Welcome (01:38) - AI Agents in the News (03:23) - From “Moltbot” to OpenClaw (04:13) - What Is OpenClaw? How It Works (05:13) - Claude Code + Agent-in-the-Middle Model (07:36) - Extending OpenClaw with Skills (08:42) - Release Timeline & Rapid Adoption (10:16) - One-Click RCE in OpenClaw (11:45) - Introducing Moltbook (AI Social Network) (14:03) - How Moltbook Actually Worked (17:55) - “I Am a Robot” & Agent Authentication (20:28) - Beaconing & Operational Behavior (26:44) - Automation vs. True Autonomy (27:26) - Control, Kill Switches & Agent Boundaries (30:59) - Workforce Impact & Near-Term Concerns (35:34) - AI Apocalypse? Final Thoughts & Wrap-Up Click here to watch this episode on YouTube. Creators & Guests Beau Bullock - Guest Hayden Covington - Guest Derek Banks - Host Brian Fehrman - Host Bronwen Aker - Host Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

AI News | Episode 39In this episode of AI Security Ops, we break down the latest developments in AI-driven threats, identity chaos caused by autonomous agents, NIST’s focus on securing AI in critical infrastructure, and new visibility tooling for AI exposure.We cover real-world abuse of LLMs for phishing, how AI agents are colliding with IAM governance, and what defenders should be watching right now.Chapters:00:00 – Introduction and SponsorsBlack Hills Information Security - https://www.blackhillsinfosec.com/Antisyphon Training - https://www.antisyphontraining.com/01:08 – LLM-Generated Phishing JavaScript (Unit 42 / Palo Alto)Discussion begins as the hosts introduce the first story.How LLMs are generating polymorphic malicious JavaScript for phishing pages and evading traditional detection.👉 https://unit42.paloaltonetworks.com/real-time-malicious-javascript-through-llms/08:49 – AI Agents vs IAM: “Who Approved This Agent?” (Hacker News)Conversation shifts to agent privilege management and governance failures.👉 https://thehackernews.com/2026/01/who-approved-this-agent-rethinking.html10:07 – NIST Focus on Securing AI Agents in Critical InfrastructureDiscussion on federal guidance and why AI agents are being treated as critical infrastructure risk components.👉 https://www.linkedin.com/pulse/cybersecurity-institute-news-roundup-20-january-2026-entrust-alz7c13:44 – Tenable One AI ExposureBreaking down Tenable’s push into enterprise AI usage visibility and exposure management.👉 https://www.tenable.com/blog/tenable-one-ai-exposure-secure-ai-usage-at-scaleJoin the 5,000+ cybersecurity professionals on our BHIS Discord server to ask questions and share your knowledge about AI Security. https://discord.gg/bhisChapters(00:00) - Introduction and Sponsors (01:08) - LLM-Generated Phishing JavaScript (Unit 42 / Palo Alto) (10:07) - NIST Focus on Securing AI Agents in Critical Infrastructure (13:44) - Tenable One AI Exposure Creators & Guests Brian Fehrman - Host Bronwen Aker - Host Click here to watch this episode on YouTube. ----------------------------------------------------------------------------------------------About Joff Thyer - https://www.blackhillsinfosec.com/team/joff-thyer/About Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/About Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/About Bronwen Aker - https://www.blackhillsinfosec.com/team/bronwen-aker/About Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com Click here to view the episode transcript.

In Episode 37 of AI Security Ops, the team breaks down the most important AI security frameworks and vulnerability databases used to track risks in machine learning and large language models. The discussion covers emerging AI vulnerability databases, the OWASP Top 10 for LLMs, CVE challenges, and frameworks like MITRE ATLAS, highlighting why standardizing AI threats is still difficult. This episode is a practical guide for security professionals looking to stay ahead of AI vulnerabilities, attack techniques, and defensive resources in a fast-moving landscape.Chapters(00:00) - Episode 37 – AI Frameworks & Databases (01:39) - A.I. vulnerability tracking is still young (02:44) - Should A.I. get its own vulnerability database? (07:33) - The benefit of multiple vulnerability databases (15:58) - The what is the definition of a vulnerability? (17:54) - Final Thoughts Brought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com🔗 Register for FREE Infosec Webcasts, Anti-casts & Summitshttps://poweredbybhis.com

AI Security Ops | Episode 35 – 2026 PredictionsIn this episode, the BHIS panel looks into the crystal ball and shares bold predictions for AI in 2026—from energy constraints and drug development breakthroughs to agentic AI risks and cybersecurity threats.Chapters(00:00) - Intro & Sponsor Shoutouts (01:14) - Prediction: Grid Power Becomes the Bottleneck (10:27) - Prediction: FDA Qualifies AI Drug Development Tools (15:45) - Prediction: Nation-State Threat Actors Weaponize AI (17:33) - Prediction: Agentic AI Dominates App Development (23:07) - Closing Thoughts: Jobs, Risk & Opportunity 🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits – https://poweredbybhis.comBrought to you by:Black Hills Information Security https://www.blackhillsinfosec.comAntisyphon Traininghttps://www.antisyphontraining.com/Active Countermeasureshttps://www.activecountermeasures.comWild West Hackin Festhttps://wildwesthackinfest.com----------------------------------------------------------------------------------------------Joff Thyer - https://blackhillsinfosec.com/team/joff-thyer/Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/Bronwen Aker - http://blackhillsinfosec.com/team/bronwen-aker/Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/