By Jeremy Hehl

Agents can triage, enrich and correlate at machine speed. But someone still has to own the risk call. On Episode 18 of EC-Council’s The Cybersecurity Podcast, Foresite Cybersecurity’s Jeremy Hehl tells host Jay Bavisi why the fully autonomous SOC is further off than vendors suggest, and why governance is the next real frontier.

Every security operations center now claims to be “AI-powered.” For MSSPs, saying anything else risks being labeled old school. So what does an agentic AI SOC actually look like in production?

Jay Bavisi, founder of EC-Council and host of The Cybersecurity Podcast, put that question to Jeremy Hehl, Chief Cybersecurity Evangelist at Foresite Cybersecurity, where he leads the company’s Google SecOps partnership. Their 40-minute conversation covered the limits of autonomy, the future of the SIEM, the fate of L1 analysts, ISO 42001, and the post-quantum risk that keeps Hehl awake at night.

Agents compute, humans decide

Hehl sees real promise in autonomous security operations. Investigation, triage, data aggregation, enrichment and correlation can already be handled by agents “pretty seamlessly,” he said. The hurdle is risk determination: deciding whether something actually matters to the business.

“The question I always ask customers who come to us and say that they want a fully autonomous SOC is: who do we fire when something goes wrong? Do we just dismiss the agent?”

Foresite’s approach treats agents as force multipliers rather than replacements. Hehl compared it to handing analysts a tricorder, a tool that scans and characterizes a threat instantly so the human can decide what to do. Bavisi summed up the model as “agents compute, human decides,” and Hehl agreed, adding that the risk call is the deciding factor.

Is the SIEM on borrowed time?

Asked why Foresite’s Google work matters when most premier SIEMs already ship with AI built in, Hehl pointed to a coming paradigm shift in where data lives. Data sovereignty, regulated industries and ever-growing telemetry volumes are straining the traditional model.

Today, a SIEM aggregates logs into a central plane, normalizes them into fields, and runs detection logic over the result. Hehl expects that to change. Logs will increasingly stay where they reside, in a hyperscaler such as Google, Azure or AWS, and agents will synthesize the raw telemetry in place.

“The idea of a SIEM may become something that is deprecated pretty rapidly.”

He likened the economics to cell phones in the 1990s, when minutes and text messages became commoditized. Data storage will become an assumption, and providers will bill for agent activity and “token burn” instead. Keeping telemetry in BigQuery, he noted, is far cheaper than keeping it hot in a separate SIEM. “The technology has to support it, and we’re not quite there yet,” he added.

The platform is also open by design. Foresite builds primarily on Google’s Vertex AI and Gemini, but Hehl said almost any model, including Claude, can be wired in through APIs and credentials. Agents are, in effect, privileged users, though wiring in other models takes real engineering, parsing and upkeep.

Is the SIEM on borrowed time?

Bavisi raised a trend seen worldwide: L1 roles vanishing, then L2, leaving only L3. Is that simply where agentic technology is heading?

Hehl said Foresite’s experience runs the other way. “We haven’t eliminated jobs. We’ve only grown,” he said. Adding agents to triage, threat hunting and analysis has let analysts handle 10 to 15 times the workload. They dismiss false positives quickly and spend the time saved on learning and more meaningful work.

He invoked the Industrial Revolution in England and France, when coal-powered textile machinery drew a Luddite backlash and even riots. Over time, workers using the machines became far more productive, and business owners demanded more output. This is the pattern known as Jevons Paradox, and Hehl sees agentic AI in the SOC following the same path.

Having started his own career red-teaming banks and working in a SOC, Hehl knows the burnout of triaging the same alert queue “over and over and over again.” Agents that correlate alerts into single cases, surface heuristic patterns and flag statistical outliers do that work “really, really well,” he said. The drudgery goes away; the analyst does not.

The few vendors promising fully autonomous SOC operations, he added, are narrow and tightly focused. Agents that reach a decision and enforce an action must be rigorously tested and simulated, and without clean data they hallucinate. Removing human control over security posture “is pretty unlikely in the next decade or so.”

Taming a non-deterministic technology

Bavisi pressed on a core engineering problem. Ask a frontier model the same question five times and you may get five different answers. How do you build a SOC on that without hallucinations and with consistent results?

Hehl’s answer: a measured, staged deployment. Start with narrow, targeted use cases where machines clearly beat humans, such as data manipulation, API access, running queries and writing code. Then build up capability and maturity step by step.

In enterprise engagements, Foresite first gets data normalization to “basically four nines.” Only then do agents go into the automation playbooks. Hehl argued that calling an agent today is not much different from calling a cloud function that once sat as Python inside a SOAR playbook.

“If you set up markdowns and guidelines and files and restrict the identity of the agent to only do very prescriptive things, as opposed to being all-encompassing, those are the outcomes that customers are looking for.”

He also described three types of MSSP customer. Some just want their brand and stakeholders protected. Some want an extension of their blue team bench. Others come to learn the “massive wall of knobs and levers” in Google’s security portfolio. Mid-market and SMB clients mostly treat agentic capability as part of the service. Enterprises usually already run agents elsewhere in the business and need a careful path to using them for security.

Governance: the next frontier for MSSPs

The industry has swung from “fire all humans and buy all the tokens” to “fire all the tokens and hire all the humans,” Bavisi observed, and is now wobbling in the middle. Where does AI governance fit for customers?

Hehl called it “the next real frontier” for managed security providers, with ISO/IEC 42001 emerging as the benchmark in the US. As public sector bodies adopt hyperscale platforms with agentic capabilities built in, they will need observability into what fleets of agents with permissive access are doing and saying to each other. That raises hard questions: where the harness sits, what protocols apply, and how to read intent from prompts and agent behavior.

“There’s a difference between an agent that sits there and does a prescriptive task … and when we start allowing agents to quantify risk and call other tools.”

He cited Wiz, which maps every model and agent in an environment and the lines of communication between them, and partner Safe AI for observability of agent activity. The CISO’s real dilemma, he said, is simple: “I’m being told I have to deploy AI. I am deploying AI. How do I secure this?”

The forgotten middle

Bavisi divided the world into three tiers. The top 5%, such as Google, Salesforce and Microsoft, have ISO 42001, red teams and consultants. At the other end are organizations that think two ChatGPT subscriptions make them an AI company. The vast majority sit in the middle. They know AI is more than chatbots but don’t know how to adopt, defend or govern it, and they cannot afford tier-one observability tools that may cost a million dollars.

How, he asked, should a business in Hokkaido, Jordan or New Zealand handle intent drift, blast radius, agent-to-agent communication and the transfer of governance between agents?

Hehl noted a related trap. Niche AI startups often build a narrow agentic product, only for the next frontier model or hyperscaler update to build that feature in and make the company irrelevant. For the mid-market, he argued, the answer is partnership: managed providers that deliver governance and observability as part of the service, “a Sherpa through the valley.”

Having ISO 42001 vs. living it

Bavisi pointed out that ISO 42001 has more than 190 controls, and as with ISO 27001, holding the certificate and operating by it are two different things. Do organizations show compliance for regulators while running with serious gaps?

“All the time,” Hehl said. Agentic adoption remains limited in US classified environments (IL-4 to IL-6) and in multinational bodies such as the European Space Agency, a Foresite client. In the commercial world, the most governed vertical with the largest gap is healthcare and life sciences, which holds sensitive patient data and research.

His prescription is to move telemetry into the cloud. Once workloads move from physical data centers into a hyperscaler, “the policies are native by default. And when agents are deployed, they’re governed by default.” The next big push, he said, is identity and privileged access management for agents, treating them as users. Bavisi added temporal context as another layer to solve.

Consolidation, and a $250,000 query

Bavisi argued the industry has a duty to bring along the businesses “where the actual civilization exists.” How? Hehl’s one-word answer: consolidation.

By around 2035, he expects hyperscalers such as Google, Microsoft and AWS, along with CrowdStrike, Palo Alto Networks, Cisco and to some extent Oracle, to keep absorbing companies and technologies. That will make enterprise-grade tooling usable by businesses of every size from one platform. Startups will keep flourishing, and Israeli startups will stay disruptive, but Hehl predicts acquisition values will fall as vibe coding lets almost anyone build a product. He also sees Chinese and Indian AI models closing the gap with American ones, with major implications for global security over the next 20 years.

On Anthropic’s Mythos, Hehl was blunt: it is “the greatest sales tool ever created.” It has stirred fears of boogeyman vulnerabilities, but he said it is genuinely capable of discovering zero-days and attack paths that need fixing. That in turn creates business for defensive tools such as Google’s CodeMender. None of it changes the basic discipline: find attack paths, shore them up, test, repeat. “We’re never really more than 99% of the way there.”

The other barrier for the middle market is cost predictability. Token-based pricing is not yet predictable. Hehl admitted Foresite once ran an accidental $250,000 query on Gemini during iterative testing and had to ask Google for forgiveness. Predictable pricing, he said, is what will let more customers lean in.

What really blocks the move to AI-era security

Asked about the biggest obstacle to moving an organization from traditional security to an AI-era culture, Hehl named three:

• Financial opacity. Customers lack transparency on what AI will actually cost.
• Unclear goals. Organizations often lack a clear picture of what they want AI to achieve, which calls for education and enablement.
• Reluctance to hand over control. Teams that have built careers around a security posture over the past decade ask why they should introduce new pain when nothing hurts now.

Winning them over is part of the “trust motion,” he said, and some will never make the shift because of requirements that keep them where they are.

Machine-speed attacks and a post-quantum dam

What keeps Hehl up at night is machine-speed attacks, which he said “are absolutely accelerating,” and frontier models built explicitly to break software and create new attacks. Beyond that is the prospect of cryptography being cracked faster than it can be rotated.

Bavisi shared the concern. He sees cracks already forming in encryption and fears the day “the dam breaks, and we’re not ready for a PQC world.” Hehl pointed to the downstream effects on blockchain, financial systems and energy grids, and the limits of what any single defender can do.

“There’s nothing we could do as an MSSP or a security practitioner to reset global cryptography … to reset the keys that we hold dear in order for us to maintain those chains of custody, privacy, and command over those systems.”

The takeaway from the conversation, Bavisi said in closing, is that the agentic SOC “is not just in the labs. It’s already in production.” The open question is whether governance, cost models and the cryptographic foundations underneath can keep up.

Watch the full episode of The Cybersecurity Podcast by EC-Council, Episode 18, featuring Jeremy Hehl.

The post Who Do We Fire When the Agent Gets It Wrong? Inside the Agentic AI SOC appeared first on CISO MAG | Cyber Security Magazine.

By Jay Bavisi, Founder & Group President, EC-Council

Nuclear treaties stopped bombs. They don’t stop a file you can email.

That’s the problem with reaching for the Nuclear Non-proliferation Treaty every time someone brings up AI risk, and last week gave everyone a reason to reach for it.

Dario Amodei published an essay arguing that the industry needs to pace itself because alignment work can’t keep up with how quickly capability is advancing now that models are helping build the next generation of models. Sam Altman agreed within hours. Elon Musk agreed in three words. Demis Hassabis agreed too and tied it back to a standards proposal DeepMind floated in July. Three men who spend most of the year competing for the same customers found, for one weekend, something to agree on.

The market didn’t wait for the philosophy to settle. By Monday, cybersecurity names including CrowdStrike, Palo Alto, Okta, Zscaler, and SentinelOne were up double digits. Semiconductor and infrastructure names sold off. Read that as the market’s actual translation of the essay: agents that can act on their own are a threat, and threats get budget. That reaction told you more about where this is headed than the essay did.

President Trump answered the next morning. The United States is leading China in AI, he said, and closed with a line that’s going to outlive most of the commentary around it: whoever wins AI wins. China’s Foreign Ministry answered within the same news cycle, calling the whole slowdown conversation fearmongering. Two governments, the only two whose cooperation a real treaty would need, both declined the premise within three days.

I’ve spent two decades building certification and training programs for the cybersecurity industry, and I’ve watched more than one generation of “we need a global framework for this” conversations play out. They rarely arrive in time to matter. So before anyone spends another year drafting a treaty that depends on Washington and Beijing agreeing to slow down together, it’s worth being honest about why the model doesn’t fit.

The NPT works, to the extent that it works, because it governs a physical thing. Uranium has to be enriched through a small number of known industrial processes, and once it is, it can be weighed, sealed, and tracked. Inspectors can put a camera on a centrifuge hall. Nobody’s smuggling a nuclear core through customs undetected.

AI doesn’t have that constraint. Once a model finishes training, what you’re actually trying to govern, its weights, is a file. It moves at the speed of a network connection. It can be copied to a laptop and walked across a border in someone’s bag. That isn’t hypothetical. It’s close to what Anthropic’s own threat reporting describes happening today. There’s no equivalent of a Significant Quantity for a neural network. No inspector can walk into a data center and certify that a company hasn’t quietly fine tuned an unmonitored version of its flagship model on a cluster the treaty never knew existed.

Even judged solely on its own terms, the NPT never reached full compliance. Four nuclear armed states sit outside it. If the best verification regime in history, pointed at the easiest possible target, still has holdouts, a treaty aimed at software is not something I’d bet a security program on.

So set the treaty down. Look at where the risk is actually piling up, because it isn’t sitting in a policy draft somewhere in Geneva. It’s sitting in poured concrete.

Global data center spending is on track to clear a trillion dollars this year, making this the largest infrastructure buildout in corporate history, and it isn’t pausing for anyone’s governance conversation. Microsoft, Amazon, and Google are signing nuclear power contracts spanning multiple decades just to keep the buildout fed. Every one of those facilities will eventually run agentic systems with real authority inside finance, healthcare, logistics, and government.

That’s the proliferation problem that actually matters. It is not weapons grade material crossing a border. It is compute, capital, and decision making authority scaling faster than most organizations’ ability to watch what they’ve built.

I’ve sat in enough boardrooms this year to put a name on the pattern: shoot first, ask questions later. A division stands up an agent to handle claims, customer support, or code review, and the governance conversation happens after the incident report, not before the rollout. IBM’s most recent Cost of a Data Breach Report puts a real number on this. Unsanctioned AI use, often called shadow AI, adds roughly $670,000 to the average cost of a breach and shows up in about one in five breaches studied. Netskope’s own 2026 data finds that a large share of enterprise generative AI traffic still runs through personal, unmanaged accounts, bypassing every control a security team thinks it has in place.

Companies are adopting this technology at press release speed and governing it at compliance calendar speed, and the gap between those two speeds is where the losses live.

A tool is not a control. I’d put that on a slide in front of any board that thinks buying an AI platform closed this risk out. It’s the 2026 version of buying a firewall in 1999 and calling the network secure. The firewall did something. It didn’t do the thing you needed.

Three words have started organizing how I think about the sequence a responsible rollout actually follows: Adopt. Defend. Govern.

Adopt, because sitting the technology out isn’t caution. It’s a slower way to lose ground. Defend, because the moment it’s live, you’re running a system capable of independent action inside your most sensitive environments, and it earns the same seriousness you’d give any system that touches money or patient data. Govern, because defense without governance is a fire extinguisher nobody’s assigned to check.

Say those three words enough times in a planning meeting, and they start reordering the meeting itself. Adoption comes first, but never by itself.

Underneath that sequence is a harder shift than most executives have made yet: moving from certifying a system once to governing it continuously. Traditional compliance assumes deterministic software. You test it, confirm that it behaves the same way every time, certify it, and revisit it next year. Agentic systems break that assumption at the root.

Run the same agent against the same task twice, and you can get two different sequences of action because the behavior is nondeterministic by design. A certificate from launch day tells you almost nothing about what that system does 200 days later, after it’s been fine tuned, wired into new tools, or handed a task nobody scoped for it up front.

That’s what people mean when they talk about a harness and context, and it’s worth saying plainly instead of leaving it as jargon. A harness is the boundary an agent operates inside. It defines what data the agent can touch, what it can do without a human, and where an action has to stop and wait for sign off before something irreversible happens.

Context is the evidence sitting underneath every one of those actions. It captures not just what the agent did, but why it was allowed to do it, under whose authority, and against which control. Put the two together, and you get something neither a treaty nor a one time audit can give you: a system that’s still governable while it’s running, not just at the moment somebody signed off on it.

None of this works without people who know how to run it, and this is where most enterprises are underinvesting relative to what they’re spending on the technology itself. I’d point to three groups.

Security teams need offensive AI ability as a baseline skill, not a specialty. For 20 years, training taught the profession to find the vulnerability, patch the system, and watch the logs while defending a target that behaved predictably. That skill isn’t going away, but it stops being sufficient once the thing you’re defending, and increasingly the thing attacking you, can act on its own and adapt during an attack.

The practical version of this is red teaming AI systems the way a penetration tester tests a network. That means testing whether a model can be manipulated through prompt injection and whether an agent’s runtime defenses hold once it’s actually wired into production tools. Anthropic’s own disclosures this year describe autonomous agents attacking targets nobody instructed them to attack. Most job descriptions haven’t caught up to that yet.
Program and IT managers need to run the full AI lifecycle, not just the launch. Most technology leaders were trained to manage a system from procurement through launch and consider the job largely finished at that point. AI doesn’t hold still that way.

Design and requirements, build and integration, deployment and change management, and incident response when something breaks all have to run as one continuous cycle because the system keeps changing after it ships. A manager who can run that whole loop is worth more right now than one who can only run the handoff.

Risk and compliance professionals need real fluency in AI governance and, specifically, in responsible AI and ethics treated as a discipline with its own evidence standard rather than as a checkbox bolted onto an existing audit. That means learning to score AI specific risk, including technical, fairness, operational, and emergent risk, against a maturity scale rather than treating it as a yes or no question.

It also means learning one methodology that maps across the frameworks companies actually get judged against: NIST’s AI risk framework, ISO’s AI management standard, the EU AI Act, and sector regulators, each using its own vocabulary for what is often the same underlying control. A risk officer who can walk into any of those conversations without starting from scratch is the difference between governance that survives an audit and governance that only survives a slide deck.

If you can’t tell me, right now, what your AI systems did in the last hour and why they were allowed to do it, you don’t have an AI program. You have a liability with good marketing.

And if the three people who’d need to answer that question, your security lead, your program manager, and your risk officer, haven’t been trained to actually answer it, the gap isn’t the technology. It’s talent, and talent is the faster problem to fix.

The treaty conversation will keep running in the background, and it should. People who work in arms control full time are better positioned than I am to carry that debate forward. But it’s not the conversation that decides whether your company has a governance failure next quarter.

That one comes down to whether the agents already running inside your business operate within a harness someone can see and are monitored by people trained to watch them, or whether they operate outside one, quietly, until the incident report explains what happened after the fact instead of before it.
There’s a harder version of this question waiting beyond the one I’ve answered here. If the capability gains Amodei described keep compounding the way he says they are, governance itself may need to be rethought from the ground up. The question will no longer be just who’s watching the agent, but what oversight even means once a system can improve itself faster than any team can review it.

That’s a different piece, and it’s coming next.

The post What the Nuclear Treaty Got Right, and Why AI Still Can’t Use It appeared first on CISO MAG | Cyber Security Magazine.

With autonomous AI agents already reaching into government systems and no global treaty in sight, EC-Council will assist any public authority that asks to map ADG 2.0’s 180+ controls to its own laws and standards

TAMPA, Fla., October 1, 2026: EC-Council today released ADG 2.0, the second version of its Adopt, Defend, Govern framework, with crosswalks to more than 90 regulations, standards, and global frameworks at no cost to any government, regulator, or standards body in the world. EC-Council will also assist any government, regulator, or standards body that reaches out, helping officials apply ADG 2.0 to their own laws, draft rules, and national standards, consistent with applicable law.

The offer comes as governments split on how to govern AI. President Trump has said concerns about AI risks are being exaggerated. China’s Foreign Ministry said that fearmongering, confrontation, and vicious competition would hamper sound global AI governance, and on September 26, Singapore’s Foreign Affairs Minister Vivian Balakrishnan urged the UN General Assembly to establish new multilateral rules, suggesting a UN Framework Convention on AI Safeguards.

Meanwhile, autonomous agents are already crossing boundaries. In July, OpenAI disclosed that models undergoing an internal cybersecurity evaluation had circumvented their testing environment and compromised parts of Hugging Face’s production infrastructure. Last week, Australia’s Prime Minister said an OpenAI agent had gained unauthorized access to a public-facing Medicare statistics portal in June. OpenAI also confirmed its agents had accessed U.S. government websites in ways it neither planned nor approved and paused training of its latest models. Separately, an independent research lab also reported a failed attempt against a Department of Education website.

“The nuclear non-proliferation treaty worked because inspectors could weigh uranium,” said Jay Bavisi, Founder, Chairman and Group CEO, EC-Council. “You can’t weigh an agent’s behavior, and no AI treaty will be signed and ratified in time to protect the systems agents are reaching today. Governments shouldn’t have to build governance from a blank page while they wait. ADG 2.0 is open, it’s already mapped to the rules they’re working with, and we’ll sit down with any government, regulator, or standards body that wants help putting it to work.”

ADG 2.0 replaces the original 12 minimum controls with more than 180 controls in 12 control families, mapped to more than 90 regulations, standards, and frameworks, including NIST AI RMF, ISO/IEC 42001, and the EU AI Act. For a regulator, the crosswalks show how a proposed national rule lines up against what other jurisdictions already require. For an enterprise, they mean working on one control set and showing how that work satisfies every rulebook it answers to, even as those rulebooks diverge.

“Most AI governance today is a policy document nobody tests,” Bavisi said. “ADG 2.0 asks for something harder. Say what you do, do what you say, and be able to prove both on any given day. That’s what a regulator, an insurer, or a board will ask for after the next incident. There will be a next incident.”

ADG is stewarded by EC-Council’s 35-member AI Advisory Board, comprising practitioners who build, secure, transform, and govern AI across some of the world’s leading organizations such as Salesforce, ServiceNow, Azure, Microsoft, Citi, JPMorgan Chase, NTT DATA, Jio Platforms, BNP Paribas Wealth Management, and others.

The framework includes:

• 180+ controls in 12 control families. One catalog covering what needs to be governed across the AI life cycle, from design and data through runtime monitoring, incident response and third-party risk.
• Mappings to 90+ regulations, standards, and frameworks. Crosswalks to sources including NIST AI RMF, ISO/IEC 42001, the EU AI Act, MITRE ATT&CK, MITRE ATLAS, the OWASP Top 10 for LLM Applications, and the OWASP Agentic Top 10.
• Runtime governance. Controls at four points in how an AI system operates, ADMIT, DECIDE, EMIT, and COMMIT, with human approval required at defined decision thresholds.
• Tiered autonomy. Assistive, Conditional, and Autonomous levels set out what an AI system may do at each level, when a human must review, and what evidence must be kept.
• Defined evidence requirements. Each control specifies the evidence it must produce, so organizations collect it while systems run rather than assemble it before an audit.
• DART implementation method. Discover, Analyze, Report, and Transform takes an organization from finding governance gaps to closing them.

Governments, regulators, and standards bodies can request assistance at adg@eccouncil.org

The ADG 2.0 framework, crosswalks, and AI Readiness Self-Assessment are available free to everyone, without registration, at AI Governance Framework (ADG) | Enterprise Agentic AI Controls

About EC-Council

Founded in 2001, EC-Council is a global cybersecurity and AI organization. It created the Certified Ethical Hacker (CEH) program and has certified more than 400,000 professionals across 174 countries. Its credentials are used across government, defense, enterprise, and academia.

As an ISO/IEC 17024 accredited certification body, EC-Council’s credentials are recognized by the U.S. Department of Defense under DoD 8140 and are held by professionals across the U.S. Army, Navy, and Air Force.

The EC-Council ecosystem includes EC-Council, EC-Council University (ECCU), CodeRed, EC-Council Global Services (EGS), EC-Council Academia, and AwareX.

Website: www.eccouncil.org

Media Contact: press@eccouncil.org

About the ADG Framework

EC-Council’s Adopt, Defend, Govern (ADG) framework is a practitioner-led operating model for AI governance. Its three pillars connect board level oversight with operational and technical controls across the AI life cycle. ADG 2.0 contains more than 180 controls in 12 control families, with crosswalks to more than 90 regulations, standards, and frameworks. It is stewarded by EC-Council’s 38 member AI Advisory Board and supported by readiness assessments and implementation guidance. Each AI Advisory board member serves in their personal capacity, and organizations are listed purely for identification. The framework, crosswalks, white paper, and self-assessment are available openly without registration or licensing requirements.

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The Westin Peachtree Plaza will anchor a week of hands-on training, offensive security research, and closed-door executive dialogue as EC-Council’s flagship events return to Georgia this October.

Atlanta will once again become a gathering point for the global cybersecurity community this fall, as EC-Council brings Hacker Halted and the Global CISO Forum back to the city for 2026. Running alongside each other at The Westin Peachtree Plaza in downtown Atlanta, the two events pair a practitioner-focused technical conference with an invitation-only executive summit, giving the industry both the hands-on depth and the strategic dialogue it needs heading into 2027.

Hacker Halted’s pre-conference training runs October 4 through 7, with the main two-day conference following on October 8 and 9. This year’s theme, “Cyber Carnival: Where Illusion Meets Intrusion,” leans into the growing role deception plays on both sides of the security fence — from adversaries weaponizing phishing kits and deepfakes to defenders learning to spot the sleight of hand before it costs them. It’s a theme that shows up directly in the speaker lineup: Perry Carpenter, KnowBe4’s Chief Deception Strategist, is among more than two dozen confirmed speakers, alongside Gary Hayslip (CISO in Residence, Halcyon.ai), Alex Holden (CISO and Founder, Hold Security), and practitioners from Amazon, Microsoft, Citi, KPMG, and Coupa Software. The agenda promises more than 20 sessions spanning offensive security, threat intelligence, AI and LLM security, incident response, and enterprise cyber risk, along with the hacking villages and breakout tracks Hacker Halted has built its reputation on.

Running on the same October 8–9 dates, the Global CISO Forum enters its fourteenth year as EC-Council’s closed-door venue for senior security leadership. Attendance is deliberately narrow: CCISO certification holders and students, EC-Council-invited practitioners, and director-level or above information security executives, with marketing and business-development attendees excluded by design. That restriction is the point. The Forum is built around closed-door sessions, curated roundtables, and off-the-record peer exchange, creating space for CISOs to talk candidly about failures and lessons learned in a way that’s harder to do on a conference main stage. For executives who qualify, it functions as the strategic counterpart to Hacker Halted’s technical program — same week, same city, different altitude of conversation.

EC-Council is also widening the door to both events this year. The organization announced complimentary conference admission to Hacker Halted and the Global CISO Forum for U.S. military and government cybersecurity professionals, covering entry to the main events while pre-conference training and optional programs remain separately priced. “Cybersecurity professionals serving government and national defense operate in environments where trust, judgment and clarity are essential,” said Jay Bavisi, EC-Council’s Founder and Group President. Phil Lopez, EC-Council’s Director of DoD/Military Affairs, framed the initiative as a matter of access: “This is about removing barriers and connecting them with practical education, trusted peers and the broader cybersecurity community.”

Taken together, the two events reflect a deliberate structure EC-Council has refined over more than a decade: a public, practitioner-driven conference that surfaces the latest offensive and defensive research, running in parallel with a private executive forum where that research gets translated into strategy. For CISOs, the pairing means a single trip to Atlanta can cover both ends of the job — staying current on how attackers are actually operating, and comparing notes with peers who are wrestling with the same board-level pressures.

Registration for Hacker Halted 2026 is open now through the event’s official site, with military and government professionals encouraged to inquire about complimentary admission directly. Global CISO Forum attendance remains by invitation, extended through EC-Council and its CCISO community.

CISO MAG members get a $49 pass to Hacker Halted and the Global CISO Forum, plus 20% off training at Hacker Halted Academy before the conference.

Use code CISOMAG49 at checkout for the $49 conference pass – Register Here

Use code CISOMAG20 at checkout for 20% off Hacker Halted Academy training – Register Here

The post Atlanta Set to Host Hacker Halted and Global CISO Forum 2026, Uniting Practitioners and C-Suite Leaders appeared first on CISO MAG | Cyber Security Magazine.