Government agencies, cybersecurity companies and threat researchers are pouring resources into studying how fast-developing AI tools can be wielded by malicious actors to hack into victim organizations.

But as agentic AI becomes more embedded in business infrastructure, there’s also a high possibility that a breach could be caused by an insider guiding the tool, whether maliciously or due to lack of security controls.

In research shared exclusively with CyberScoop, DTEX researchers detail how a common workflow in Anthropic’s Claude Cowork used in corporate environments offers convenience for AI agent deployment but grants near-total access to the system.

Claude Cowork includes tools that let users remotely control their agents. One particular tool, known as Dispatch, relays commands from a user’s phone to their desktop Claude agent. It also includes a plugin for communicating with Salesforce AI agents that access and transfer data.

DTEX researchers tested two scenarios. The first prompted Claude to summarize information from Salesforce and paste it into a draft Outlook email. The second tasked the agent with archiving selected files and transferring them via the Cowork app.

In both cases, researchers used simple, single-turn prompts and spent between 10-30 minutes preparing to exfil  the data.

Alex Desmond, director of insider threat intelligence and innovation at DTEX, told CyberScoop that both improvements in frontier models and deeper integration of AI tools into IT network operations have reduced the time defenders have to react to a breach.

“In cyberattacks, you talk about the kind of execution time of adversaries coming in and dropping ransomware, we’re now seeing the kill chain drop to 30 and 10 minutes depending on what they’re doing,” Desmond said. “Six months ago, that was a couple of hours.”

But that speed, when paired with direct access to business networks or cloud services, can also create an insider threat nightmare for organizations that must monitor for both malicious actors and potential mistakes from legitimate employees using the technology.

Over the past few years, western IT and cybersecurity businesses have been inundated with job applicants secretly working on behalf of the North Korean government. Their salaries are used to evade international sanctions and fund Pyongyang’s nuclear program, but it also positions the individuals to access or steal sensitive data or assets from these companies. 

“You’ve got a nation-state actor getting into an environment legitimately,” Desmond said. “Now if you gave them access to AI tools on top of that…you’re like ‘here’s the keys to everything and here’s this awesome tool that’s just going to make your job – stealing our data – easier.’”

Tests by DTEX confirmed that the agents indeed had access to sensitive systems, applications and data – including the ability to download SharePoint corporate data, production documentation in OneDrive, access to Outlook email, Salesforce data (and all the data it can access), and any other files on the user’s endpoint device. For each of these applications, Claude Cowork has a dedicated plugin or API to share externally if prompted.  

To be clear, DTEX’s research does not involve exploiting a software bug or configuration vulnerability, and it doesn’t come with a CVE. It’s more of an IT governance and visibility problem. Businesses are racing to integrate AI tools into their workflow and pushing employees to use the technology while failing to put in place the kind of security controls, access policies and monitoring required to spot problems.

For instance, it may not be possible to determine how a data breach or leakage involving an AI agent actually occurred if an organization is not logging and auditing its prompts – or whether the incident was the result of an agent running amok or responding to potentially malicious instructions.

While network and cloud monitoring can identify when data is being accessed or downloaded from SharePoint, that may not be a strong enough signal to stand out for defenders.

“If a user’s normal workflow is to pull sensitive files down to work locally all the time, you don’t have endpoint monitoring and you introduce an AI agent, it then just has access to all that data” along with the ability to exfiltrate it,” Desmond said.

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On Wednesday, Microsoft released two new red teaming tools — Rampart and Clarity — meant to help developers design more secure agentic software and assist incident responders in the face of ongoing breaches.

Rampart is built on top of PyRIT, an existing open automation framework Microsoft developed for red teaming generative AI systems. But while PyRIT scans already-built systems for security flaws, Rampart is made to continuously test code for vulnerabilities during the development process, encoding both adversarial and benign testing scenarios into the software development pipeline to flag exploitable bugs and dependencies.

Microsoft said Rampart was built to focus on cross-prompt injection attacks, where “an agent retrieves or processes potentially poisoned content from documents, emails, tickets, and other data sources that manipulate behavior indirectly.” It also confirms fixes or exploits work as intended through multiple rounds of testing, as opposed to tools that perform “single shot validation.”

The second tool, Clarity, can be run as a desktop app, a web interface or directly embedded into a coding agent to provide real time security engineering guidance to developers at the outset of a project. It can categorize and track different business objectives related to the code and highlight downstream security implications along with more secure by design alternatives.

Ram Shankar Siva Kumar, who founded Microsoft’s AI red team in 2019, told CyberScoop that the company has seen internal security benefits from using the tools, but believesRampart and Clarity’s growth depends on contributions from other developers outside the Microsoft ecosystem.

In the fast-moving world of AI, where vibe coding, rogue AI agents and a steady churn of new model releases create fresh security implications nearly every week, Siva Kumar said it was important to begin building foundational, AI-centric security processes into the software development pipeline.

“When you hear a lot of talk about AI safety and security, it seems to be a lot of philosophical debates,” he said. “You’ll see frameworks, you’ll see white papers, and I think we’re really past that time, now. We really need to start thinking of AI safety as an engineering discipline and trying to bring security where the developers are.”

Rampart’s potential utility to defenders goes beyond just securing software development pipelines. It can also be used during an active incident response to speed up or automate red teaming for hot fixes, patching and remediation.

Microsoft has used Rampart when investigating reported vulnerabilities in their own products. Siva Kumar said the tool was able to help condense a week’s worth of manual work —  replicating the vulnerability, identifying different variants of the same bug, then patching and re-testing those variants to ensure they’re no longer exploitable — into hours.

Clarity, meanwhile, acts as a security adviser for software projects, prompting developers to consider potential risks in their design decisions and their downstream security consequences. With the rise of AI-generated code and agents, and execution becoming cheaper, this kind of proactive guidance is increasingly important.

“You’re going to be able to create apps, create MCP servers to pull things out from the internet,” said Siva Kumar. “The question is, ‘should you be doing it?’ And Clarity is a step in that direction. It is asking, ‘hey, should you be doing this in the first place?’”

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As organizations consider agentic AI for their business and IT stacks, researchers continue to find bugs and vulnerabilities in major, commercial models  that can significantly expand their attack surface.

This week, researchers at Pillar Security disclosed a vulnerability in Antigravity, an AI-powered developer tool for filesystem operations made by Google.

The bug, since patched, combined prompt injection with Antigravity’s permitted file-creation capability to grant attackers remote code execution privileges.

The research details how the exploit was able to circumvent Antigravity’s secure mode, Google’s highest security setting for its agents that runs all command operations through a virtual sandbox environment, throttles network access and prohibits the agent from writing code outside of the working directory.

Secure mode is supposed to limit the AI agent access to sensitive systems – and its ability to execute malicious or dangerous acts through shell commands. But one of the file-searching tools used by Antigravity, called “find_by_name,” is classified as a ‘native’ system tool. This means the agent can execute it directly and before protections like Secure Mode can even evaluate command level operations.

“The security boundary that Secure Mode enforces simply never sees this call,” wrote Dan Lisichkin, an AI security researcher with Pillar Security. “This means an attacker achieves arbitrary code execution under the exact configuration a security-conscious user would rely on to prevent it.”

The prompt injection attacks can be delivered through compromised identity accounts connected to the agent, or indirectly by hiding clandestine prompt instructions inside open-source files or web content the agent ingests. Antigravity  has trouble distinguishing between written data it ingests for context and literal prompt instructions, so compromise can be achieved without any elevated access by getting it to read a malicious document or file.

According to a disclosure timeline provided by Pillar Security, the bug was reported to Google on Jan. 6 and patched on Feb. 28, with Google awarding a bug bounty for the discovery.

Lisichkin said this same pattern of prompt injection through unvalidated input has been found in other coding AI agents like Cursor. In the age of AI, any unvalidated input can become a malicious prompt capable of hijacking internal systems.

“The trust model underpinning security assumptions, that a human will catch something suspicious, does not hold when autonomous agents follow instructions from external content,” he wrote.

The fact that the vulnerability was able to completely bypass Google’s secure mode underscores how the cybersecurity industry must start adapting and “move beyond sanitization-based controls.” 

“Every native tool parameter that reaches a shell command is a potential injection point. Auditing for this class of vulnerability is no longer optional, and it is a prerequisite for shipping agentic features safely,” Lisichkin wrote.

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North Korean threat groups are using artificial intelligence tools to accelerate and expand the country’s long-running scheme to get remote technical workers hired at global companies for longer durations, Microsoft Threat Intelligence said in a report Friday. 

AI services are empowering North Korean operatives across the attack lifecycle. Attackers have turned AI into a “force multiplier” that bolsters and automates their efforts to conduct research on targets, develop malicious resources, achieve and maintain access, evade detection, and weaponize tools for attacks and post-compromise activities, researchers said.

Microsoft said a trio of groups it tracks as Coral Sleet, Sapphire Sleet and Jasper Sleet are using AI to shorten the time it takes to create digital personas for specific job markets and roles. These groups frequently leverage financial opportunities or interview-themed lures to gain initial access.

Jasper Sleet is using generative AI tools to research job postings on platforms such as Upwork, and identify in-demand skills or experience requirements to align fake personas with targeted roles, Microsoft said in the report.

Researchers warned that threat groups are also “significantly improving the scale and sophistication of their social engineering and initial access operations” with AI-driven media creation for impersonations and real-time voice modulation. 

North Korean threat groups have used AI services to generate lures that mimic internal communications in multiple languages with native fluency. 

“These technologies enable threat actors to craft highly tailored, convincing lures and personas at unprecedented speed and volume, which lowers the barrier for complex attacks to take place and increases the likelihood of successful compromise,” researchers wrote in the report. 

Microsoft has observed Jasper Sleet using the AI application Faceswap to insert North Korean IT workers’ faces into stolen identity documents, in some cases reusing the same AI-generated photo across multiple personas.

Jasper Sleet is also leaning on AI-enabled communications after an operative is successfully hired by a victim organization to evade detection and sustain long-term employment. Microsoft has observed North Korean remote IT workers prompting AI tools to craft professional responses, answer technical questions or generate snippets of code to meet performance expectations in unfamiliar environments.

North Korean threat groups are using AI to refine previously observed post-compromise activities, reducing the time and expertise required for decision-making, Microsoft said. These AI-powered tasks accelerate analysis of unfamiliar compromised environments, identify viable paths for lateral movement and enable operatives to blend in with legitimate activity. 

North Korean threat groups are also using AI to escalate privileges, locate and steal sensitive records or credentials, and minimize risk of detection by analyzing security controls.

Generative AI composes most threat activity involving AI, but Microsoft said a transition to agentic AI is underway. 

“For threat actors, this shift could represent a meaningful change in tradecraft by enabling semi‑autonomous workflows that continuously refine phishing campaigns, test and adapt infrastructure, maintain persistence, or monitor open‑source intelligence for new opportunities,” researchers wrote in the report. 

“Microsoft has not yet observed large-scale use of agentic AI by threat actors, largely due to ongoing reliability and operational constraints,” researchers added. Yet, Microsoft warned, experiments illustrate the potential agentic AI systems pose for more advanced and damaging activity.

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