How this CISO sells confidence amid constant breach headlines
▼ Summary
– Engineers using AI coding assistants create agents that inherit their creators’ over-provisioned access, expanding the security risk.
– When engineers leave, undocumented agents they built continue running, creating an inverted bus-factor problem with no record of their function.
– AI aids defense through log analysis and policy drafting, but autonomous SOCs are unrealistic because AI lacks business context and human judgment.
– For services provider Span, a breach response becomes a product demonstration, requiring proof of controls and containment to protect reputation.
– The cybersecurity talent gap is misframed: entry-level applicants are abundant, but senior practitioners are scarce, and automated tooling threatens junior roles that build future experts.
Engineering teams across enterprise IT are now writing their own software using AI coding assistants, deploying autonomous agents that act on their behalf, and granting those agents the same access privileges as their human creators. This fundamental shift has thrust the chief information security officer (CISO) into uncharted territory that barely existed two years ago. Speaking at the Span Cyber Security Arena conference, Hrvoje Englman, CISO at Span, explained how this evolution is reshaping what defenders prioritize most.
Span’s workforce includes a substantial number of developers, alongside an even larger group of engineers. The engineers represent the new wild card. With AI-assisted coding, they are building applications and personal agents to automate parts of their daily work. Each new agent inherits the identity of its creator, and those identities are typically over-provisioned. The principle of least privilege remains an aspiration that is notoriously difficult to enforce in live production environments.
“I cannot be the blocker,” Englman said. “You cannot block progress. People will find ways around it.” His approach focuses on enabling secure use of AI within the company rather than trying to prohibit it outright.
The bus-factor problem multiplies
The risk goes far beyond access control. When a single engineer automates a business process using five interacting agents and then leaves for another job, the organization inherits an undocumented system that no one understands. Englman called this an inversion of the traditional bus-factor problem. In the past, a key person leaving created a knowledge gap. Now, the agents they built keep running, and the company has no record of what they do or why.
Defender’s leverage is real, with limits
AI has delivered concrete gains in defensive work. Englman highlighted log analysis as one area where the value is immediate. Feeding hundreds of megabytes of log files into an AI tool and asking it to surface anomalies or pivot on an IP address compresses work that previously took analysts hours. Policy drafting is another strong use case. Generating a first draft from internal context can cut a three-day task down to a single day, and the time savings compound across the workforce.
He drew a sharper line on the vendor pitch for autonomous AI-driven security operations centers (SOCs). The idea of defensive AI battling offensive AI in real time, with no humans in the loop, does not match what is achievable today. Log ingestion remains the hardest part of running a SOC, and detection engineering still depends on people who can explain why an alert fired.
“You get an alert, but your analyst doesn’t understand the alert,” Englman said, describing the failure mode he sees in teams that lean too heavily on automated tooling. “And you have two million alerts, and then what?” Autonomous isolation of systems remains out of reach because the AI does not understand the underlying business process. Decisions about when to shut down a critical service get escalated to senior leadership during real incidents, and that judgment stays with humans.
He also pushed back on the industry’s framing of breaches. Most of the largest incidents trace back to phishing and credential theft. Vendors selling AI-powered SOCs as a defense against nation-state actors are addressing a smaller part of the problem than their marketing suggests.
The threat model for a services provider
Span sells IT services to enterprise clients, which doubles its exposure. The company is a target in its own right and a target for attackers seeking access to its customers. A typical end-user organization can absorb a breach and recover. For Span, the response itself becomes the product on display.
Englman said the company must be able to demonstrate that controls were in place, that the failure was contained, and that the incident was handled with the same discipline it offers customers. Reputation is what gets sold, and negligence would end the business.
Skills shortage, restated
The widely discussed cybersecurity talent gap, in Englman’s view, is misframed. Entry-level applicants are abundant. Senior practitioners with five or more years of operational depth are scarce, and that gap cannot be closed quickly through training programs. The Span Cyber Security Center has trained more than 3,000 people, and Englman said the pipeline matters precisely because the industry’s push toward automated tooling threatens to eliminate the junior roles where future experts get built.
His measure for a SOC analyst centers on whether they can explain what the alert means and how the conditions that triggered it came about. Without that understanding, an analyst rolling a fifty-fifty guess on relevance is no better than a model doing the same.
The wisdom he has discarded
Asked which piece of conventional security wisdom he has stopped believing, Englman named the framing of humans as the weakest link in the chain. He called it lazy and a form of blame culture. The responsibility, he said, sits with the CISO to build systems where a user clicking a malicious link does not bring the environment down. Brittle defenses that depend on perfect human behavior are a design failure.
(Source: Help Net Security)
