What Is an Agentic SOC?

An agentic SOC is a security operations center in which AI agents carry out the work of a Security Operations Center (SOC). This typically includes: gathering context, correlating evidence across tools, forming hypotheses, drafting conclusions, and, where trust has been earned, acting. The term entered common usage in 2025 and became the default vocabulary for AI driven security operations in 2026, as security teams confronted a problem that human staffing cannot solve: attacks now move at machine speed, and defense conducted at human speed loses on tempo alone.

The problem it answers

A SOC analyst investigating a single alert typically touches a SIEM, an EDR console, identity logs, threat intelligence, and a ticketing system, spending most of the investigation gathering context rather than exercising judgment. Multiply that by thousands of daily alerts and the arithmetic fails. Attackers transformed themselves before defenders. AI powered attacks compress exploitation windows from weeks to minutes, rotate infrastructure faster than blocklists update, and generate variants faster than signatures can be written. The asymmetry is economic: attack became cheap, and investigation stayed expensive. The purpose of an agentic SOC is to reverse that asymmetry, raising the marginal cost of attack while lowering the marginal cost of prevention and response.

What distinguishes an agent from a playbook

SOAR platforms promised automation a decade ago and delivered it for the predictable slice of SOC work. A playbook is a script: if these conditions, then these steps. However a SOAR cannot handle the case nobody anticipated, and increasingly the cases that matter include some portion of novelty. An agent differs in kind. Given a goal, such as determining whether a login pattern represents account takeover, it selects tools, interprets intermediate results, changes course when evidence surprises it, and produces a reasoned conclusion a human can audit. The practical distinction: playbooks encode answers, agents conduct inquiries.

Architecture of an agentic SOC

A working agentic SOC has three layers. First, a detection substrate that decides what deserves attention. Second, agents that investigate what the substrate surfaces: enriching, correlating, reconstructing the sequence of events, mapping behavior to MITRE ATT&CK, and drafting the case. Third, connective tissue to the tools the SOC already runs, increasingly standardized through the Model Context Protocol (MCP), so agents can query the SIEM, the EDR, identity providers, and ticketing without bespoke integrations.

The hardest layer to transform is likely the first: detections. An agentic SOC wrapped around a general purpose LLM inherits that model's understanding of security telemetry, which is shallow, and its false positive rate, which is high. Agents investigating bad findings produce fast, articulate, wrong conclusions. This is why DeepTempo pairs Vigil, its agentic SOC, with LogLM, a cybersecurity foundation model: an encoder only transformer trained broadly across security logs and telemetry that surfaces behavioral anomalies rules and signatures miss, with zero shot proficiency. The agents are only as good as what they are pointed at.

Earned autonomy

The uncomfortable question in every agentic SOC evaluation is authority: what is this system permitted to do without asking? The answer that survives contact with production is graduated. Attempt, verify, repeat. Agents begin by drafting and recommending while humans decide. As the record accumulates, and only for actions where the record justifies it, the SOC delegates. This is not a hedge; it is the same discipline that made infrastructure automation trustworthy. The DeepTempo team learned it building StackStorm, the open source event driven automation platform adopted by large enterprises, and carried the lesson into Vigil's design. Autonomy granted before it is earned is how automation incidents happen and can set back a SOC transformation by months or years.

Why open source is structural, not incidental

An agentic SOC asks for something no security product has asked for before: delegated judgment. That request changes what transparency is worth. When the agents, prompts, playbooks, and integrations are open source, as Vigil's are under the Apache 2.0 license, a security team can read exactly what the system will do, extend it to fit its environment, and run it where its data lives, including on premises and air gapped. Vigil ships with 13 specialized agents, more than 30 MCP integrations, and a community rule set exceeding 7,200 detections. The alternative, a proprietary black box exercising judgment over your incidents in someone else's cloud, requires a degree of faith that regulated and sovereignty conscious organizations cannot extend.

Perhaps just as importantly as owning the guardrails, and hence clarity on execution, is the unprecedented improvement in the efficacy of the models themselves. Enterprises and other large users are able to capture these benefits themselves by using the open source Vigil as opposed to sharing them with their security vendors.

And in today's environment, increasingly users are uncomfortable sending their logs and other telemetry, and especially their context, to remote vendors. An open source solution like Vigil runs easily within the existing environment, under the user's control.

Measurement over assertion

The agentic SOC market is crowded with claims and short on evidence. The corrective is open benchmarking. SOCBench, an open benchmark for detection and response efficacy, measures precision, recall, false positives, ATT&CK coverage, cost, and drift, and applies the same yardstick to DeepTempo's own stack. Buyers evaluating any agentic SOC, including Vigil, should insist on measured results against their own historical telemetry rather than demonstrations on curated data.

Where this is heading

Search interest in agentic SOC and autonomous security has climbed steeply through 2026, alongside interest in AI zero day exploitation and autonomous malware, and the pairing is not a coincidence. Machine speed offense makes machine speed defense a requirement rather than an option. The organizing question for the next several years is not whether SOCs adopt agents, but whether those agents rest on detection foundations worthy of them, earn their autonomy honestly, and prove their efficacy in the open.

See it on your own telemetry

Reading about an agentic SOC is one thing; watching one work your own historical logs is another. DeepTempo offers a free threat hunt: a 30 day Detection Assessment that runs LogLM against your telemetry and reports what your current stack missed, findings your team keeps either way. Request a Detection Assessment.