Episodios

  • LiteLLM Supply Chain Compromise | Episode 47

    LiteLLM Supply Chain Compromise | Episode 47
    Apr 13 2026

    In this episode of BHIS Presents: AI Security Ops, the team breaks down the LiteLLM supply chain compromise–a real-world attack that shows how AI systems are being breached through the same old software supply chain weaknesses.

    What initially looked like a bad release quickly escalated into a full-scale compromise affecting a library downloaded millions of times per day. But LiteLLM wasn’t the starting point–it was just one link in a much larger attack chain involving compromised security tools, CI/CD pipelines, and stolen publishing credentials.

    The result? Malicious packages distributed at scale, harvesting secrets, enabling lateral movement, and establishing persistence across affected systems.

    We dig into:
    • What LiteLLM is and why it’s such a high-value target
    • How the attack chain started with compromised security tooling (Trivy, Checkmarx)
    • How unpinned dependencies enabled the compromise
    • The role of CI/CD pipelines in exposing sensitive credentials
    • What the malicious LiteLLM packages actually did (credential harvesting, persistence, lateral movement)
    • The scale of impact given LiteLLM’s widespread adoption
    • Why supply chain attacks are no longer theoretical–and no longer nation-state exclusive
    • How AI is lowering the barrier to entry for attackers
    • Why this wasn’t really an “AI vulnerability”–but an infrastructure failure
    • The growing risk of automated, agent-driven attack discovery

    This episode highlights a critical reality: the biggest risks in AI systems aren’t always in the models–they’re in the pipelines, dependencies, and infrastructure surrounding them.

    ⸻

    📚 Key Concepts & Topics

    Supply Chain Security
    • Dependency poisoning and malicious package distribution
    • CI/CD pipeline compromise
    • Version pinning and build integrity

    Credential & Secrets Exposure
    • API keys, SSH keys, and cloud credentials in pipelines
    • Risks of centralized AI gateways like LiteLLM

    Threat Actor Techniques
    • Tag rewriting and trusted reference hijacking
    • Multi-stage malware (harvest, lateral movement, persistence)
    • Use of lookalike domains for exfiltration

    AI & Security Reality Check
    • AI as an amplifier, not the root vulnerability
    • Traditional security failures in modern AI stacks
    • Automation lowering attacker barriers

    Defensive Strategies
    • Dependency pinning and isolation (Docker, VPS)
    • Atomic credential rotation
    • Treating CI/CD tools as critical infrastructure
    • Monitoring outbound traffic from build environments


    • (00:00) - Intro & Incident Overview
    • (01:26) - What Is LiteLLM & Why It Matters
    • (03:53) - Supply Chain Scope & Why This Is Dangerous
    • (07:31) - Why These Attacks Are Getting Easier (AI + Scale)
    • (10:48) - Attack Chain Breakdown (Trivy → Checkmarx → LiteLLM)
    • (11:50) - What the Malware Did & Impact at Scale
    • (14:23) - Detection, Response & Who Was Safe

    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.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

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    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
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    Click here to view the episode transcript.
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    20 m
  • Model Ablation | Episode 46

    Model Ablation | Episode 46
    Apr 2 2026

    In this episode of BHIS Presents: AI Security Ops, the team breaks down model ablation — a powerful interpretability technique that’s quickly becoming a serious concern in AI security.

    What started as a way to better understand how models work is now being used to remove safety mechanisms entirely. By identifying and disabling specific components inside a model, researchers — and attackers — can effectively strip out refusal behavior while leaving the rest of the model fully functional.

    The result? A fast, reliable way to “de-safety” AI systems without prompt engineering, fine-tuning, or significant compute.

    We dig into:
    • What model ablation is and how it works
    • The difference between ablation and pruning
    • How safety behaviors can be isolated inside model internals
    • Why refusal mechanisms are often localized (and fragile)
    • How ablation is being used as a jailbreak technique
    • Why this is more reliable than prompt-based attacks
    • Risks specific to open-weight models and public checkpoints
    • The growing “uncensored model” ecosystem
    • Why interpretability is a double-edged sword
    • Whether safety should be deeply embedded into model architecture
    • What this means for defenders and AI security strategy

    This episode explores a critical shift in AI risk: when safety controls can be surgically removed, they stop being security controls at all.

    ⸻

    📚 Key Concepts & Topics

    Model Internals & Interpretability
    • Neurons, attention heads, and residual stream analysis
    • Activation space and feature directions

    AI Security Risks
    • Prompt injection vs. structural attacks
    • Jailbreaking techniques and safety bypasses

    Model Access & Risk Surface
    • Open-weight vs. API-only models
    • Hugging Face and the uncensored model ecosystem

    AI Safety & Governance
    • Defense-in-depth for AI systems
    • Future standards for ablation resistance

    #AISecurity #ModelAblation #LLMSecurity #CyberSecurity #ArtificialIntelligence #AIResearch #BHIS #AIAgents #InfoSec

    • (00:00) - Intro & Show Overview
    • (01:27) - Removing AI Safety Mechanisms
    • (02:05) - What Is Model Ablation? (Technical Breakdown)
    • (04:01) - Open-Weight Models & Practical Limitations
    • (05:43) - Risks, Use Cases, and Ethical Tradeoffs
    • (07:32) - Security Implications & “You Can’t Ban Math”
    • (10:43) - Future Impact: Open Models Catching Up
    • (17:44) - Final Takeaway: Why “No” Isn’t Security

    Click here to watch this episode on YouTube.

    Creators & Guests
    • Bronwen Aker - Host
    • Derek Banks - Host
    • Brian Fehrman - Host

    Brought to you by:

    Black Hills Information Security

    https://www.blackhillsinfosec.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

    https://wildwesthackinfest.com

    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
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    Click here to view the episode transcript.
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    18 m
  • Embedding Space Attacks | Episode 45

    Embedding Space Attacks | Episode 45
    Mar 26 2026

    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 stores

    This 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 Covered

    AI Foundations
    - Embeddings and vector representations
    - Similarity search and vector space reasoning

    AI Security Risks
    - Embedding space manipulation
    - Data poisoning in vector databases
    - Retrieval manipulation in RAG systems

    Applications & Impact
    - LLM-powered search and assistants
    - AI pipelines using embeddings
    - Risks in production AI systems

    #AISecurity #Embeddings #CyberSecurity #LLMSecurity #AIThreats #BHIS #AIAgents #ArtificialIntelligence #InfoSec

    Join 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.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

    https://wildwesthackinfest.com

    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
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    Click here to view the episode transcript.
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    33 m
  • Indirect Prompt Injection | Episode 44

    Indirect Prompt Injection | Episode 44
    Mar 19 2026
    In this episode of BHIS Presents: AI Security Ops, the team breaks down indirect prompt injection — the #1 risk in the OWASP Top 10 for LLM Applications — and why it represents one of the most dangerous and misunderstood threats in modern AI systems.Unlike traditional attacks, indirect prompt injection doesn’t require malware, credentials, or even user interaction. Instead, attackers hide malicious instructions inside everyday content like emails, documents, or web pages — and wait for AI systems to unknowingly execute them.From real-world exploits like EchoLeak to in-the-wild attacks observed by Palo Alto Unit 42, this episode explores how attackers are already abusing AI-powered tools in production environments — and why current defenses are struggling to keep up.We dig into:• What indirect prompt injection is and how it differs from direct attacks• Why OWASP ranks prompt injection as the #1 LLM security risk• How attackers hide payloads inside emails, documents, and web content• The EchoLeak zero-click exploit against Microsoft 365 Copilot• Web-based prompt injection attacks observed in the wild (Unit 42)• Exploits targeting AI coding tools like Cursor IDE and GitHub Copilot• How RAG systems amplify the risk through poisoned knowledge bases• Why LLM architecture makes this problem fundamentally hard to solve• Research showing modern defenses still fail 50%+ of the time• Practical mitigation strategies: least privilege, human-in-the-loop, and observabilityThis episode focuses on the real-world security implications of AI adoption, showing how attackers are already leveraging these techniques — and what defenders need to understand as AI becomes deeply embedded in business workflows.⸻📚 Key ReferencesPrompt Injection & LLM Risk• OWASP Top 10 for LLM Applications 2025 — https://owasp.orgReal-World Attacks• EchoLeak (CVE-2025-32711) — Aim Security / arXiv• Unit 42 — Web-Based Indirect Prompt Injection in the Wild (March 2026) — https://unit42.paloaltonetworks.comAI System Vulnerabilities• Cursor IDE (CVE-2025-59944)• GitHub Copilot (CVE-2025-53773)• Lakera — Zero-Click MCP Attack — https://lakera.aiResearch on Defenses• Zhan et al. — Adaptive Attacks Break Defenses (NAACL 2025)• Anthropic System Card (Feb 2026)• Google Gemini Security Research (2025)Standards & Guidance• NIST AI Risk Management Framework — https://nist.gov• MITRE ATLAS — https://atlas.mitre.org• ISO/IEC 42001 AI Management Systems#AISecurity #PromptInjection #CyberSecurity #LLMSecurity #AIThreats #BHIS #AIAgents #ArtificialIntelligence #infosec (00:00) - Intro & BHIS / Antisyphon Overview(01:19) - OWASP Top 10 & Prompt Injection Context(01:41) - Indirect Prompt Injection Explained (Stored Attack Analogy)(02:54) - Real-World Attack Scenarios (Calendar & Hidden Payloads)(05:10) - EchoLeak & Zero-Click Copilot Exploit(06:10) - Weaponized Excel Prompt Injection PoC(06:50) - Email Injection & AI Summarization Abuse(09:07) - Why Detection & Prevention Are So Difficult(14:02) - Mitigations & Final ThoughtsClick here to watch this episode on YouTube. Creators & Guests Derek Banks - HostBrian Fehrman - HostBrought 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.
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    16 m
  • Top AI Security Concerns | Episode 43

    Top AI Security Concerns | Episode 43
    Mar 12 2026
    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(02:41) - Agentic AI as a Security Threat (CrowdStrike 2026 Global Threat Report, IBM X-Force Index)(04:09) - Malicious Agent Skills & AI Supply Chain Attacks (Cisco State of AI Security)(05:21) - How Agent Skills Actually Work(08:10) - Permissions & Guardrails for AI Agents (CISA AI in OT Guidance)(10:20) - AI-Generated Phishing Campaigns (CrowdStrike / IBM Threat Reports)(14:21) - Deepfakes at Industrial Scale (WEF Global Cybersecurity Outlook)(16:01) - Corporate Fraud & Deepfake Incidents (International AI Safety Report)(17:44) - Why Humans Struggle to Detect Deepfakes(21:36) - Prompt Injection Attacks Explained (Schneier – Promptware Kill Chain)(24:58) - AI Models Jailbreaking Other Models (Palo Alto Unit 42 Research)(29:22) - Final Thoughts & Wrap-UpClick here to watch this episode on YouTube. Creators & Guests Bronwen Aker - HostBrian Fehrman - HostBrought 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. 🧦 SOC Summit 2026https://www.antisyphontraining.com/event/soc-summit/
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    29 m
  • Claude Cowork Discussion | Episode 42

    Claude Cowork Discussion | Episode 42
    Mar 6 2026

    We discuss the meaning of AI life In episode 42 of "BHIS Presents: AI Security Ops." Derek Banks is joined by Bronwen Aker and Brian Fehrman to break down Anthropic’s latest agentic desktop experiment: Claude Cowork.

    Claude Cowork brings large language models directly onto the endpoint — giving Claude the ability to read, write, and organize files on your local machine. It’s designed to make powerful AI workflows accessible to non-technical users… but as with any tool that operates at the OS level, the security implications are significant.

    We explore what happens when AI moves closer to your data, your filesystem, and your browser — and what that means for defenders.

    We dig into:
    - What Claude Cowork is and how it differs from Claude Code
    - Agentic desktop tools vs. command-line workflows
    - Local file access and OS-level interaction risks
    - Skills, automation, and task iteration
    - Chrome plugins and expanded attack surface
    - Overly broad permissions and least-privilege concerns
    - SaaS disruption and shifting trust boundaries
    - Endpoint monitoring challenges
    - The speed of AI releases vs. security review cycles
    - Balancing innovation with responsible deployment

    This conversation looks at the real-world operational and defensive considerations of agentic AI tools running directly on user systems. If you’re evaluating AI productivity tools inside your organization — or defending environments where they’re already being adopted — this episode will help you think through the risks and tradeoffs.

    • (00:00) - Intro & Episode Overview
    • (02:08) - What Is Claude Cowork?
    • (04:03) - Desktop Agents vs. Command Line Users
    • (06:12) - Agentic Workflows & Task Automation
    • (08:08) - Building Fast with Claude (Speed of Development)
    • (09:29) - Browser Plugins & Expanding Capabilities
    • (11:06) - Permission Models & “Just Give It Access to Everything”
    • (12:40) - SaaS Disruption & Enterprise Impact
    • (14:38) - Overly Broad File Access Risks
    • (16:27) - Organizational Disruption & Workforce Impact
    • (18:09) - Security Lag vs. Rapid AI Releases
    • (19:46) - Final Thoughts & Wrap-Up

    Click here to watch this episode on YouTube.

    Creators & Guests
    • Derek Banks - Host
    • Bronwen Aker - Host
    • Brian Fehrman - Host

    Brought to you by:

    Black Hills Information Security

    https://www.blackhillsinfosec.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

    https://wildwesthackinfest.com

    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
    https://poweredbybhis.com

    Click here to view the episode transcript.
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    22 m
  • OpenClaw and Moltbook with Guests Beau Bullock and Hayden Covington | Episode 41

    OpenClaw and Moltbook with Guests Beau Bullock and Hayden Covington | Episode 41
    Feb 26 2026

    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 works
    • AI agents operating other AI systems (Claude Code in the loop)
    • The concept of “skills” and extending agent capabilities
    • The one-click RCE vulnerability discovered shortly after release
    • Moltbook as a social network for AI agents
    • API keys, agent-only access, and how humans bypassed it
    • Beacons, autonomy, and what “control” really means
    • Where the line is between automation and true autonomy
    • Short-term workforce impacts vs. long-term AI risk


    This 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
    • (02:01) - AI Agents in the News
    • (03:46) - From “Moltbot” to OpenClaw
    • (04:36) - What Is OpenClaw? How It Works
    • (05:36) - Claude Code + Agent-in-the-Middle Model
    • (07:59) - Extending OpenClaw with Skills
    • (09:05) - Release Timeline & Rapid Adoption
    • (10:39) - One-Click RCE in OpenClaw
    • (12:08) - Introducing Moltbook (AI Social Network)
    • (14:26) - How Moltbook Actually Worked
    • (18:18) - “I Am a Robot” & Agent Authentication
    • (20:51) - Beaconing & Operational Behavior
    • (27:07) - Automation vs. True Autonomy
    • (27:49) - Control, Kill Switches & Agent Boundaries
    • (31:22) - Workforce Impact & Near-Term Concerns
    • (35:57) - 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.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

    https://wildwesthackinfest.com

    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
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    Click here to view the episode transcript.


    🧦 SOC Summit 2026
    https://www.antisyphontraining.com/event/soc-summit/
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    36 m
  • AI in the SOC: Interview with Hayden Covington and Ethan Robish from the BHIS SOC | Episode 40

    AI in the SOC: Interview with Hayden Covington and Ethan Robish from the BHIS SOC | Episode 40
    Feb 20 2026

    AI in the SOC: Interview with Hayden Covington and Ethan Robish from the BHIS SOC | Episode 40

    In this episode of BHIS Presents: AI Security Ops, we sit down with Hayden Covington and Ethan Robish from the BHIS Security Operations Center (SOC) to explore how AI is actually being used in modern defensive operations.

    From foundational machine learning techniques like statistical baselining and clustering to large language models assisting with alert triage and reporting, we dig into what works, what doesn’t, and what SOC teams should realistically expect from AI today.

    We break down:

    - How AI helps reduce alert fatigue and improve triage
    - Practical automation inside a real-world SOC
    - The difference between traditional ML approaches and LLM-powered workflows
    - Foundational techniques like K-means, anomaly detection, and behavioral baselining
    - Using LLMs for enrichment, investigation, and report drafting
    - Where AI struggles: hallucinations, inconsistency, and edge cases
    - Risks around over-trusting AI in security operations
    - How to responsibly integrate AI into analyst workflows

    This episode is grounded in real operational experience—not vendor demos. If you’re running a SOC, building AI tooling, or just trying to separate hype from reality, this conversation will help you think clearly about augmentation vs. automation in defensive security.


    • (00:00) - Intro & Guest Introductions
    • (04:44) - Alert Triage & SOC Pain Points
    • (06:04) - Automation Inside the SOC
    • (09:59) - “Boring AI”: Clustering, Baselining & Statistics
    • (17:06) - AI-Assisted Reporting & Client Communication
    • (18:34) - Limitations, Edge Cases & Model Risk
    • (22:56) - Hallucinations & Inconsistent Outputs
    • (25:04) - AI Demos vs. Real-World Security Work
    • (28:35) - Final Thoughts & Closing

    Click here to watch this episode on YouTube.

    Creators & Guests
    • Hayden Covington - Guest
    • Ethan Robish - Guest
    • Bronwen Aker - Host
    • Derek Banks - Host
    • Brian Fehrman - Host

    Brought to you by:

    Black Hills Information Security

    https://www.blackhillsinfosec.com


    Antisyphon Training

    https://www.antisyphontraining.com/


    Active Countermeasures

    https://www.activecountermeasures.com


    Wild West Hackin Fest

    https://wildwesthackinfest.com

    🔗 Register for FREE Infosec Webcasts, Anti-casts & Summits
    https://poweredbybhis.com

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    29 m