Agentic AI Security: Keep Your Cyber Hygiene Failures from Becoming a Global Breach

The Claude Code weaponization reveals the true threat: The democratization and orchestration of existing attack capabilities. It proves that neglecting fundamental cyber hygiene allows malicious AI to execute massive-scale attacks with unprecedented speed and low skill.

Beneath all the novelty of the recent Claude incident — it compromised AI! it was autonomous! it was nation-state espionage! — lies a longstanding and fundamental reality: Organizations are unable to sustain basic cybersecurity hygiene. The attack ultimately relied on tried and true tactics, techniques, and procedures and existing tools.

Let’s be clear: The Nov. 13 disclosure by Anthropic marks the start of a new era from which there is no turning back. At the same time, it shines a light on issues that have challenged security teams for years. The urgency for preemptive exposure management has never been higher.

The Attack: Agentic AI's role and execution

Novel orchestration, tried and true tactics

The autonomy and scale of this attack is stunning. Anthropic reports a China state-sponsored group it calls GTG-1002 used agentic AI to manage autonomous cyber attacks against approximately 30 organizations, succeeding in a small number of cases. The group employed “social engineering” against an AI model so it circumvented its training and behaved harmfully at scale. It’s the first verified case of agentic AI obtaining access to confirmed high-value targets for espionage, including major technology corporations and government agencies. But it’s not the first reported case of Claude Code abuse. In August, Anthropic detailed how Claude Code was weaponized to “an unprecedented degree” in a large-scale extortion and data-theft campaign.

At the same time, we can’t overlook the fact that Claude Code was manipulated to execute the same tasks threat actors have been using for years:

• Attack surface mapping
• Service discovery
• Vulnerability discovery
• Payload generation
• Credential extraction
• Lateral movement based on discovered infrastructure
• Data extraction

And it used existing tools to do so. 

Understanding the threat model

The AI was effectively an uber-orchestration and automation tool that enabled all of this to happen on a shocking scale. GTG-1002 made use of readily available tools and existing flaws and misconfigurations in their targets’ environments to execute attacks at a scale impossible with human intervention. Based on the available reporting, it does not appear that any traditional inherent code vulnerabilities in Claude itself were exploited. Instead, the attackers pretended to be someone who they weren’t, and exploited the model's susceptibility to task decomposition — a behavioral characteristic that allowed it to be manipulated into performing harmful steps. An AI built by humans fell prey to a version of social engineering — a tactic involved in 22% of breaches, according to the 2025 Verizon Data Breach Investigations Report.

The democratization of cyber attack capabilities

Leveraging existing open source tools and flaws

According to Anthropic’s case study, “The operational infrastructure relied overwhelmingly on open source penetration testing tools rather than custom malware development. Standard security utilities including network scanners, database exploitation frameworks, password crackers, and binary analysis suites comprised the core technical toolkit.”

The custom automation frameworks built around Model Context Protocol (MCP) servers focused on integration rather than novel capabilities. This allowed the framework’s AI agents to execute remote commands, coordinate multiple tools simultaneously, and maintain persistent operational state, according to the report. “The custom development of the threat actor’s framework focused on integration rather than novel capabilities,” the report states.

This means the capabilities are already available; anyone should be able to do this.

Multiple specialized model context protocol (MCP) servers provided interfaces between Claude and various tool categories:

• Remote command execution on dedicated penetration testing systems
• Browser automation for web application reconnaissance
• Code analysis for security assessment
• Testing framework integration for systematic vulnerability validation
• Callback communication for out-of-band exploitation confirmation

This reduces the learning curve. Expect less advanced actors to wage more sophisticated attacks with the broad availability of these kits.

The reality: AI as an attack amplifier

To fully grasp the paradigm shift AI represents, we must recognize that the danger is not in entirely novel attack methods, but in an increase in operational speed and scale — the true power of orchestration.

Consider the history of cryptography during World War II. The famous code-breaking machines, like the British Bombe and the U.S. Navy’s Rapid Analytical Machinery (RAM) devices, were highly specialized calculators that pushed the limits of computation. Their game-changing advantage was not what they could do but how fast they could operate. By automating thousands of tedious calculations per second, they stripped away the time-intensive process of manual cryptanalysis, accelerating the existing process far beyond human capability. They did not invent a new cipher-breaking technique; they simply accelerated and orchestrated the effort.

Similarly, today’s malicious AI tools are not yet inventing fundamentally new flaws in our architecture — yet they are providing threat actors with an automated and scalable orchestration engine that turns days, weeks, or months of reconnaissance, targeting, and tool selection into hours, drastically lowering the skill and time barriers.

The Claude case is only the beginning. It will serve as an amplifier for adversarial operations moving forward. It’s another issue defenders now have to deal with at scale, just as they currently deal with the sheer scale of vulnerabilities and the number of new CVEs being disclosed daily.

Conclusion: Adjusting cybersecurity strategy post Nov. 13

The question now is: How do you adjust your cybersecurity strategy post Nov. 13

When we think about defense against an adversary like this, the old rules still apply, but they are no longer sufficient. We need a new playbook, one rooted in a preemptive exposure management strategy.

— Blake Kizer, Senior Staff Information Security Engineer, Tenable, "A Practical Defense Against AI-Led Attacks"

The vendor's responsibility: Better safeguards

Vendors need to have better safeguards. When we think about defense against an adversary like this, the old rules still apply, but they are no longer sufficient. We need a new playbook. Existing guardrails should be improved to detect attacker attempts to bypass them. Guardrails should detect payload splitting and task decomposition, rate limit suspicious events, and identify social engineering attempts.

The practitioner's priority: Preemptive exposure management

The Claude incident underscores the importance of understanding your environment and where you’re exposed, and how to mitigate the risks associated with that exposure. Practicing preemptive security is a step in the right direction. We’ve been talking for years about the dangers of learned helplessness, the risks of failing to patch known exploited vulnerabilities, and the harm from misconfigurations and overprivileged accounts. These risks are not new. What’s new is that agentic AI allows exploitation on an unprecedented scale. Even an AI-orchestrated attack can’t succeed without the vulnerabilities, misconfigurations, and excessive permissions needed for lateral movement and privilege escalation. Security is a foundational responsibility of all cybersecurity practitioners. Elevating the standard of basic security hygiene is essential for our collective defense. The time for complacency is long past; the time to be preemptive is now.